10 Search Results for "Li, Tianqi"

Document
RANDOM
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2024.41
Hilbert Functions and Low-Degree Randomness Extractors

Authors: Alexander Golovnev, Zeyu Guo, Pooya Hatami, Satyajeet Nagargoje, and Chao Yan

Published in: LIPIcs, Volume 317, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024)

Abstract
For S ⊆ 𝔽ⁿ, consider the linear space of restrictions of degree-d polynomials to S. The Hilbert function of S, denoted h_S(d,𝔽), is the dimension of this space. We obtain a tight lower bound on the smallest value of the Hilbert function of subsets S of arbitrary finite grids in 𝔽ⁿ with a fixed size |S|. We achieve this by proving that this value coincides with a combinatorial quantity, namely the smallest number of low Hamming weight points in a down-closed set of size |S|. Understanding the smallest values of Hilbert functions is closely related to the study of degree-d closure of sets, a notion introduced by Nie and Wang (Journal of Combinatorial Theory, Series A, 2015). We use bounds on the Hilbert function to obtain a tight bound on the size of degree-d closures of subsets of 𝔽_qⁿ, which answers a question posed by Doron, Ta-Shma, and Tell (Computational Complexity, 2022). We use the bounds on the Hilbert function and degree-d closure of sets to prove that a random low-degree polynomial is an extractor for samplable randomness sources. Most notably, we prove the existence of low-degree extractors and dispersers for sources generated by constant-degree polynomials and polynomial-size circuits. Until recently, even the existence of arbitrary deterministic extractors for such sources was not known.
Cite as

Alexander Golovnev, Zeyu Guo, Pooya Hatami, Satyajeet Nagargoje, and Chao Yan. Hilbert Functions and Low-Degree Randomness Extractors. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 317, pp. 41:1-41:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{golovnev_et_al:LIPIcs.APPROX/RANDOM.2024.41,
  author =	{Golovnev, Alexander and Guo, Zeyu and Hatami, Pooya and Nagargoje, Satyajeet and Yan, Chao},
  title =	{{Hilbert Functions and Low-Degree Randomness Extractors}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024)},
  pages =	{41:1--41:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-348-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{317},
  editor =	{Kumar, Amit and Ron-Zewi, Noga},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2024.41},
  URN =		{urn:nbn:de:0030-drops-210345},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2024.41},
  annote =	{Keywords: Extractors, Dispersers, Circuits, Hilbert Function, Randomness, Low Degree Polynomials}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.29
Generalizing Shape Analysis with Gradual Types

Authors: Zeina Migeed, James Reed, Jason Ansel, and Jens Palsberg

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Tensors are multi-dimensional data structures that can represent the data processed by machine learning tasks. Tensor programs tend to be short and readable, and they can leverage libraries and frameworks such as TensorFlow and PyTorch, as well as modern hardware such as GPUs and TPUs. However, tensor programs also tend to obscure shape information, which can cause shape errors that are difficult to find. Such shape errors can be avoided by a combination of shape annotations and shape analysis, but such annotations are burdensome to come up with manually. In this paper, we use gradual typing to reduce the barrier of entry. Gradual typing offers a way to incrementally introduce type annotations into programs. From there, we focus on tool support for type migration, which is a concept that closely models code-annotation tasks and allows us to do shape reasoning and utilize it for different purposes. We develop a comprehensive gradual typing theory to reason about tensor shapes. We then ask three fundamental questions about a gradually typed tensor program. (1) Does the program have a static migration? (2) Given a program and some arithmetic constraints on shapes, can we migrate the program according to the constraints? (3) Can we eliminate branches that depend on shapes? We develop novel tools to address the three problems. For the third problem, there are currently two PyTorch tools that aim to eliminate branches. They do so by eliminating them for just a single input. Our tool is the first to eliminate branches for an infinite class of inputs, using static shape information. Our tools help prevent bugs, alleviate the burden on the programmer of annotating the program, and improves the process of program transformation.
Cite as

Zeina Migeed, James Reed, Jason Ansel, and Jens Palsberg. Generalizing Shape Analysis with Gradual Types. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 29:1-29:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{migeed_et_al:LIPIcs.ECOOP.2024.29,
  author =	{Migeed, Zeina and Reed, James and Ansel, Jason and Palsberg, Jens},
  title =	{{Generalizing Shape Analysis with Gradual Types}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{29:1--29:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.29},
  URN =		{urn:nbn:de:0030-drops-208786},
  doi =		{10.4230/LIPIcs.ECOOP.2024.29},
  annote =	{Keywords: Tensor Shapes, Gradual Types, Migration}
}
Document
DOI: 10.4230/LIPIcs.DNA.30.1
Geometric Enumeration of Localized DNA Strand Displacement Reaction Networks

Authors: Matthew R. Lakin and Sarika Kumar

Published in: LIPIcs, Volume 314, 30th International Conference on DNA Computing and Molecular Programming (DNA 30) (2024)

Abstract
Localized molecular devices are a powerful tool for engineering complex information-processing circuits and molecular robots. Their practical advantages include speed and scalability of interactions between components tethered near to each other on an underlying nanostructure, and the ability to restrict interactions between more distant components. The latter is a critical feature that must be factored into computational tools for the design and simulation of localized molecular devices: unlike in solution-phase systems, the geometries of molecular interactions must be accounted for when attempting to determine the network of possible reactions in a tethered molecular system. This work aims to address that challenge by integrating, for the first time, automated approaches to analysis of molecular geometry with reaction enumeration algorithms for DNA strand displacement reaction networks that can be applied to tethered molecular systems. By adapting a simple approach to solving the biophysical constraints inherent in molecular interactions to be applicable to tethered systems, we produce a localized reaction enumeration system that enhances previous approaches to reaction enumeration in tethered system by not requiring users to explicitly specify the subsets of components that are capable of interacting. This greatly simplifies the user’s task and could also be used as the basis of future systems for automated placement or routing of signal-transmission and logical processing in molecular devices. We apply this system to several published example systems from the literature, including both tethered molecular logic systems and molecular robots.
Cite as

Matthew R. Lakin and Sarika Kumar. Geometric Enumeration of Localized DNA Strand Displacement Reaction Networks. In 30th International Conference on DNA Computing and Molecular Programming (DNA 30). Leibniz International Proceedings in Informatics (LIPIcs), Volume 314, pp. 1:1-1:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{lakin_et_al:LIPIcs.DNA.30.1,
  author =	{Lakin, Matthew R. and Kumar, Sarika},
  title =	{{Geometric Enumeration of Localized DNA Strand Displacement Reaction Networks}},
  booktitle =	{30th International Conference on DNA Computing and Molecular Programming (DNA 30)},
  pages =	{1:1--1:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-344-7},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{314},
  editor =	{Seki, Shinnosuke and Stewart, Jaimie Marie},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DNA.30.1},
  URN =		{urn:nbn:de:0030-drops-209294},
  doi =		{10.4230/LIPIcs.DNA.30.1},
  annote =	{Keywords: Localized circuits, reaction enumeration, DNA strand displacement, geometry, molecular computing}
}
Document
DOI: 10.4230/LIPIcs.SAT.2024.16
Towards Universally Accessible SAT Technology

Authors: Alexey Ignatiev, Zi Li Tan, and Christos Karamanos

Published in: LIPIcs, Volume 305, 27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024)

Abstract
Boolean satisfiability (SAT) solvers are a family of highly efficient reasoning engines, which are frequently used for solving a large and diverse variety of practical challenges. This applies to multidisciplinary problems belonging to the class NP but also those arising at higher levels of the polynomial hierarchy. Unfortunately, encoding a problem of user’s interest to a (series of) propositional formula(s) in conjunctive normal form (CNF), let alone dealing with a SAT solver, is rarely a simple task even for an experienced SAT practitioner. This situation gets aggravated further when the user has little to no knowledge on the operation of the modern SAT solving technology. In 2018, the PySAT framework was proposed to address the issue of fast and "painless" prototyping with SAT solvers in Python allowing researchers to get SAT-based solutions to their problems without investing substantial time in the development process and yet sacrificing only a little in terms of performance. Since then, PySAT has proved a useful instrument for solving a wide range of practical problems and is now a critical package for the PyPI infrastructure. In the meantime, there have been advances in SAT solving and enhancements to PySAT functionality to extend its modelling and solving capabilities in order to make modern SAT technology accessible and deployable on a massive scale. This paper provides a high-level overview of the current architecture of PySAT and some of its capabilities including arbitrary Boolean formula manipulation, CNF preprocessing, and support for external user-defined propagators.
Cite as

Alexey Ignatiev, Zi Li Tan, and Christos Karamanos. Towards Universally Accessible SAT Technology. In 27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 305, pp. 16:1-16:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{ignatiev_et_al:LIPIcs.SAT.2024.16,
  author =	{Ignatiev, Alexey and Tan, Zi Li and Karamanos, Christos},
  title =	{{Towards Universally Accessible SAT Technology}},
  booktitle =	{27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024)},
  pages =	{16:1--16:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-334-8},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{305},
  editor =	{Chakraborty, Supratik and Jiang, Jie-Hong Roland},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2024.16},
  URN =		{urn:nbn:de:0030-drops-205382},
  doi =		{10.4230/LIPIcs.SAT.2024.16},
  annote =	{Keywords: PySAT, Python, Prototyping, Practical Applicability}
}
Document
DOI: 10.4230/LIPIcs.SAT.2024.30
Anytime Approximate Formal Feature Attribution

Authors: Jinqiang Yu, Graham Farr, Alexey Ignatiev, and Peter J. Stuckey

Published in: LIPIcs, Volume 305, 27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024)

Abstract
Widespread use of artificial intelligence (AI) algorithms and machine learning (ML) models on the one hand and a number of crucial issues pertaining to them warrant the need for explainable artificial intelligence (XAI). A key explainability question is: given this decision was made, what are the input features which contributed to the decision? Although a range of XAI approaches exist to tackle this problem, most of them have significant limitations. Heuristic XAI approaches suffer from the lack of quality guarantees, and often try to approximate Shapley values, which is not the same as explaining which features contribute to a decision. A recent alternative is so-called formal feature attribution (FFA), which defines feature importance as the fraction of formal abductive explanations (AXp’s) containing the given feature. This measures feature importance from the view of formally reasoning about the model’s behavior. Namely, given a system of constraints logically representing the ML model of interest, computing an AXp requires finding a minimal unsatisfiable subset (MUS) of the system. It is challenging to compute FFA using its definition because that involves counting over all AXp’s (equivalently, counting over MUSes), although one can approximate it. Based on these results, this paper makes several contributions. First, it gives compelling evidence that computing FFA is intractable, even if the set of contrastive formal explanations (CXp’s), which correspond to minimal correction subsets (MCSes) of the logical system, is provided, by proving that the problem is #P-hard. Second, by using the duality between MUSes and MCSes, it proposes an efficient heuristic to switch from MCS enumeration to MUS enumeration on-the-fly resulting in an adaptive explanation enumeration algorithm effectively approximating FFA in an anytime fashion. Finally, experimental results obtained on a range of widely used datasets demonstrate the effectiveness of the proposed FFA approximation approach in terms of the error of FFA approximation as well as the number of explanations computed and their diversity given a fixed time limit.
Cite as

Jinqiang Yu, Graham Farr, Alexey Ignatiev, and Peter J. Stuckey. Anytime Approximate Formal Feature Attribution. In 27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 305, pp. 30:1-30:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{yu_et_al:LIPIcs.SAT.2024.30,
  author =	{Yu, Jinqiang and Farr, Graham and Ignatiev, Alexey and Stuckey, Peter J.},
  title =	{{Anytime Approximate Formal Feature Attribution}},
  booktitle =	{27th International Conference on Theory and Applications of Satisfiability Testing (SAT 2024)},
  pages =	{30:1--30:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-334-8},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{305},
  editor =	{Chakraborty, Supratik and Jiang, Jie-Hong Roland},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2024.30},
  URN =		{urn:nbn:de:0030-drops-205526},
  doi =		{10.4230/LIPIcs.SAT.2024.30},
  annote =	{Keywords: Explainable AI, Formal Feature Attribution, Minimal Unsatisfiable Subsets, MUS Enumeration}
}
Document
DOI: 10.4230/LIPIcs.CCC.2024.10
Explicit Directional Affine Extractors and Improved Hardness for Linear Branching Programs

Authors: Xin Li and Yan Zhong

Published in: LIPIcs, Volume 300, 39th Computational Complexity Conference (CCC 2024)

Abstract
Affine extractors give some of the best-known lower bounds for various computational models, such as AC⁰ circuits, parity decision trees, and general Boolean circuits. However, they are not known to give strong lower bounds for read-once branching programs (ROBPs). In a recent work, Gryaznov, Pudlák, and Talebanfard (CCC' 22) introduced a stronger version of affine extractors known as directional affine extractors, together with a generalization of ROBPs where each node can make linear queries, and showed that the former implies strong lower bound for a certain type of the latter known as strongly read-once linear branching programs (SROLBPs). Their main result gives explicit constructions of directional affine extractors for entropy k > 2n/3, which implies average-case complexity 2^{n/3-o(n)} against SROLBPs with exponentially small correlation. A follow-up work by Chattopadhyay and Liao (CCC' 23) improves the hardness to 2^{n-o(n)} at the price of increasing the correlation to polynomially large, via a new connection to sumset extractors introduced by Chattopadhyay and Li (STOC' 16) and explicit constructions of such extractors by Chattopadhyay and Liao (STOC' 22). Both works left open the questions of better constructions of directional affine extractors and improved average-case complexity against SROLBPs in the regime of small correlation. This paper provides a much more in-depth study of directional affine extractors, SROLBPs, and ROBPs. Our main results include: - An explicit construction of directional affine extractors with k = o(n) and exponentially small error, which gives average-case complexity 2^{n-o(n)} against SROLBPs with exponentially small correlation, thus answering the two open questions raised in previous works. - An explicit function in AC⁰ that gives average-case complexity 2^{(1-δ)n} against ROBPs with negligible correlation, for any constant δ > 0. Previously, no such average-case hardness is known, and the best size lower bound for any function in AC⁰ against ROBPs is 2^Ω(n). One of the key ingredients in our constructions is a new linear somewhere condenser for affine sources, which is based on dimension expanders. The condenser also leads to an unconditional improvement of the entropy requirement of explicit affine extractors with negligible error. We further show that the condenser also works for general weak random sources, under the Polynomial Freiman-Ruzsa Theorem in 𝖥₂ⁿ, recently proved by Gowers, Green, Manners, and Tao (arXiv' 23).
Cite as

Xin Li and Yan Zhong. Explicit Directional Affine Extractors and Improved Hardness for Linear Branching Programs. In 39th Computational Complexity Conference (CCC 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 300, pp. 10:1-10:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{li_et_al:LIPIcs.CCC.2024.10,
  author =	{Li, Xin and Zhong, Yan},
  title =	{{Explicit Directional Affine Extractors and Improved Hardness for Linear Branching Programs}},
  booktitle =	{39th Computational Complexity Conference (CCC 2024)},
  pages =	{10:1--10:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-331-7},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{300},
  editor =	{Santhanam, Rahul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2024.10},
  URN =		{urn:nbn:de:0030-drops-204060},
  doi =		{10.4230/LIPIcs.CCC.2024.10},
  annote =	{Keywords: Randomness Extractors, Affine, Read-once Linear Branching Programs, Low-degree polynomials, AC⁰ circuits}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2024.108
Two-Source and Affine Non-Malleable Extractors for Small Entropy

Authors: Xin Li and Yan Zhong

Published in: LIPIcs, Volume 297, 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)

Abstract
Non-malleable extractors are generalizations and strengthening of standard randomness extractors, that are resilient to adversarial tampering. Such extractors have wide applications in cryptography and have become important cornerstones in recent breakthroughs of explicit constructions of two-source extractors and affine extractors for small entropy. However, explicit constructions of non-malleable extractors appear to be much harder than standard extractors. Indeed, in the well-studied models of two-source and affine non-malleable extractors, the previous best constructions only work for entropy rate > 2/3 and 1-γ for some small constant γ > 0 respectively by Li (FOCS' 23). In this paper, we present explicit constructions of two-source and affine non-malleable extractors that match the state-of-the-art constructions of standard ones for small entropy. Our main results include: - Two-source and affine non-malleable extractors (over 𝖥₂) for sources on n bits with min-entropy k ≥ log^C n and polynomially small error, matching the parameters of standard extractors by Chattopadhyay and Zuckerman (STOC' 16, Annals of Mathematics' 19) and Li (FOCS' 16). - Two-source and affine non-malleable extractors (over 𝖥₂) for sources on n bits with min-entropy k = O(log n) and constant error, matching the parameters of standard extractors by Li (FOCS' 23). Our constructions significantly improve previous results, and the parameters (entropy requirement and error) are the best possible without first improving the constructions of standard extractors. In addition, our improved affine non-malleable extractors give strong lower bounds for a certain kind of read-once linear branching programs, recently introduced by Gryaznov, Pudlák, and Talebanfard (CCC' 22) as a generalization of several well studied computational models. These bounds match the previously best-known average-case hardness results given by Chattopadhyay and Liao (CCC' 23) and Li (FOCS' 23), where the branching program size lower bounds are close to optimal, but the explicit functions we use here are different. Our results also suggest a possible deeper connection between non-malleable extractors and standard ones.
Cite as

Xin Li and Yan Zhong. Two-Source and Affine Non-Malleable Extractors for Small Entropy. In 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 297, pp. 108:1-108:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{li_et_al:LIPIcs.ICALP.2024.108,
  author =	{Li, Xin and Zhong, Yan},
  title =	{{Two-Source and Affine Non-Malleable Extractors for Small Entropy}},
  booktitle =	{51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)},
  pages =	{108:1--108:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-322-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{297},
  editor =	{Bringmann, Karl and Grohe, Martin and Puppis, Gabriele and Svensson, Ola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2024.108},
  URN =		{urn:nbn:de:0030-drops-202512},
  doi =		{10.4230/LIPIcs.ICALP.2024.108},
  annote =	{Keywords: Randomness Extractors, Non-malleable, Two-source, Affine}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2023.35
Black-Box Constructive Proofs Are Unavoidable

Authors: Lijie Chen, Ryan Williams, and Tianqi Yang

Published in: LIPIcs, Volume 251, 14th Innovations in Theoretical Computer Science Conference (ITCS 2023)

Abstract
Following Razborov and Rudich, a "natural property" for proving a circuit lower bound satisfies three axioms: constructivity, largeness, and usefulness. In 2013, Williams proved that for any reasonable circuit class C, NEXP ⊂ C is equivalent to the existence of a constructive property useful against C. Here, a property is constructive if it can be decided in poly(N) time, where N = 2ⁿ is the length of the truth-table of the given n-input function. Recently, Fan, Li, and Yang initiated the study of black-box natural properties, which require a much stronger notion of constructivity, called black-box constructivity: the property should be decidable in randomized polylog(N) time, given oracle access to the n-input function. They showed that most proofs based on random restrictions yield black-box natural properties, and demonstrated limitations on what black-box natural properties can prove. In this paper, perhaps surprisingly, we prove that the equivalence of Williams holds even with this stronger notion of black-box constructivity: for any reasonable circuit class C, NEXP ⊂ C is equivalent to the existence of a black-box constructive property useful against C. The main technical ingredient in proving this equivalence is a smooth, strong, and locally-decodable probabilistically checkable proof (PCP), which we construct based on a recent work by Paradise. As a by-product, we show that average-case witness lower bounds for PCP verifiers follow from NEXP lower bounds. We also show that randomness is essential in the definition of black-box constructivity: we unconditionally prove that there is no deterministic polylog(N)-time constructive property that is useful against even polynomial-size AC⁰ circuits.
Cite as

Lijie Chen, Ryan Williams, and Tianqi Yang. Black-Box Constructive Proofs Are Unavoidable. In 14th Innovations in Theoretical Computer Science Conference (ITCS 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 251, pp. 35:1-35:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{chen_et_al:LIPIcs.ITCS.2023.35,
  author =	{Chen, Lijie and Williams, Ryan and Yang, Tianqi},
  title =	{{Black-Box Constructive Proofs Are Unavoidable}},
  booktitle =	{14th Innovations in Theoretical Computer Science Conference (ITCS 2023)},
  pages =	{35:1--35:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-263-1},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{251},
  editor =	{Tauman Kalai, Yael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2023.35},
  URN =		{urn:nbn:de:0030-drops-175380},
  doi =		{10.4230/LIPIcs.ITCS.2023.35},
  annote =	{Keywords: Circuit lower bounds, natural proofs, probabilistic checkable proofs}
}
Document
DOI: 10.4230/LIPIcs.CCC.2022.23
Extremely Efficient Constructions of Hash Functions, with Applications to Hardness Magnification and PRFs

Authors: Lijie Chen, Jiatu Li, and Tianqi Yang

Published in: LIPIcs, Volume 234, 37th Computational Complexity Conference (CCC 2022)

Abstract
In a recent work, Fan, Li, and Yang (STOC 2022) constructed a family of almost-universal hash functions such that each function in the family is computable by (2n + o(n))-gate circuits of fan-in 2 over the B₂ basis. Applying this family, they established the existence of pseudorandom functions computable by circuits of the same complexity, under the standard assumption that OWFs exist. However, a major disadvantage of the hash family construction by Fan, Li, and Yang (STOC 2022) is that it requires a seed length of poly(n), which limits its potential applications. We address this issue by giving an improved construction of almost-universal hash functions with seed length polylog(n), such that each function in the family is computable with POLYLOGTIME-uniform (2n + o(n))-gate circuits. Our new construction has the following applications in both complexity theory and cryptography. - (Hardness magnification). Let α : ℕ → ℕ be any function such that α(n) ≤ log n / log log n. We show that if there is an n^{α(n)}-sparse NP language that does not have probabilistic circuits of 2n + O(n/log log n) gates, then we have (1) NTIME[2ⁿ] ⊈ SIZE[2^{n^{1/5}}] and (2) NP ⊈ SIZE[n^k] for every constant k. Complementing this magnification phenomenon, we present an O(n)-sparse language in P which requires probabilistic circuits of size at least 2n - 2. This is the first result in hardness magnification showing that even a sub-linear additive improvement on known circuit size lower bounds would imply NEXP ⊄ P_{/poly}. Following Chen, Jin, and Williams (STOC 2020), we also establish a sharp threshold for explicit obstructions: we give an explict obstruction against (2n-2)-size circuits, and prove that a sub-linear additive improvement on the circuit size would imply (1) DTIME[2ⁿ] ⊈ SIZE[2^{n^{1/5}}] and (2) P ⊈ SIZE[n^k] for every constant k. - (Extremely efficient construction of pseudorandom functions). Assuming that one of integer factoring, decisional Diffie-Hellman, or ring learning-with-errors is sub-exponentially hard, we show the existence of pseudorandom functions computable by POLYLOGTIME-uniform AC⁰[2] circuits with 2n + o(n) wires, with key length polylog(n). We also show that PRFs computable by POLYLOGTIME-uniform B₂ circuits of 2n + o(n) gates follows from the existence of sub-exponentially secure one-way functions.
Cite as

Lijie Chen, Jiatu Li, and Tianqi Yang. Extremely Efficient Constructions of Hash Functions, with Applications to Hardness Magnification and PRFs. In 37th Computational Complexity Conference (CCC 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 234, pp. 23:1-23:37, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

Copy BibTex To Clipboard

@InProceedings{chen_et_al:LIPIcs.CCC.2022.23,
  author =	{Chen, Lijie and Li, Jiatu and Yang, Tianqi},
  title =	{{Extremely Efficient Constructions of Hash Functions, with Applications to Hardness Magnification and PRFs}},
  booktitle =	{37th Computational Complexity Conference (CCC 2022)},
  pages =	{23:1--23:37},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-241-9},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{234},
  editor =	{Lovett, Shachar},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2022.23},
  URN =		{urn:nbn:de:0030-drops-165852},
  doi =		{10.4230/LIPIcs.CCC.2022.23},
  annote =	{Keywords: Almost universal hash functions, hardness magnification, pseudorandom functions}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2020.36
An Efficient Algorithm for 1-Dimensional (Persistent) Path Homology

Authors: Tamal K. Dey, Tianqi Li, and Yusu Wang

Published in: LIPIcs, Volume 164, 36th International Symposium on Computational Geometry (SoCG 2020)

Abstract
This paper focuses on developing an efficient algorithm for analyzing a directed network (graph) from a topological viewpoint. A prevalent technique for such topological analysis involves computation of homology groups and their persistence. These concepts are well suited for spaces that are not directed. As a result, one needs a concept of homology that accommodates orientations in input space. Path-homology developed for directed graphs by Grigoryan, Lin, Muranov and Yau has been effectively adapted for this purpose recently by Chowdhury and Mémoli. They also give an algorithm to compute this path-homology. Our main contribution in this paper is an algorithm that computes this path-homology and its persistence more efficiently for the 1-dimensional (H₁) case. In developing such an algorithm, we discover various structures and their efficient computations that aid computing the 1-dimensional path-homology. We implement our algorithm and present some preliminary experimental results.
Cite as

Tamal K. Dey, Tianqi Li, and Yusu Wang. An Efficient Algorithm for 1-Dimensional (Persistent) Path Homology. In 36th International Symposium on Computational Geometry (SoCG 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 164, pp. 36:1-36:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

Copy BibTex To Clipboard

@InProceedings{dey_et_al:LIPIcs.SoCG.2020.36,
  author =	{Dey, Tamal K. and Li, Tianqi and Wang, Yusu},
  title =	{{An Efficient Algorithm for 1-Dimensional (Persistent) Path Homology}},
  booktitle =	{36th International Symposium on Computational Geometry (SoCG 2020)},
  pages =	{36:1--36:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-143-6},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{164},
  editor =	{Cabello, Sergio and Chen, Danny Z.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2020.36},
  URN =		{urn:nbn:de:0030-drops-121944},
  doi =		{10.4230/LIPIcs.SoCG.2020.36},
  annote =	{Keywords: computational topology, directed graph, path homology, persistent path homology}
}
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