6 Search Results for "Chen, Yi"


Document
On the Power of Nonstandard Quantum Oracles

Authors: Roozbeh Bassirian, Bill Fefferman, and Kunal Marwaha

Published in: LIPIcs, Volume 266, 18th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2023)


Abstract
We study how the choices made when designing an oracle affect the complexity of quantum property testing problems defined relative to this oracle. We encode a regular graph of even degree as an invertible function f, and present f in different oracle models. We first give a one-query QMA protocol to test if a graph encoded in f has a small disconnected subset. We then use representation theory to show that no classical witness can help a quantum verifier efficiently decide this problem relative to an in-place oracle. Perhaps surprisingly, a simple modification to the standard oracle prevents a quantum verifier from efficiently deciding this problem, even with access to an unbounded witness.

Cite as

Roozbeh Bassirian, Bill Fefferman, and Kunal Marwaha. On the Power of Nonstandard Quantum Oracles. In 18th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 266, pp. 11:1-11:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{bassirian_et_al:LIPIcs.TQC.2023.11,
  author =	{Bassirian, Roozbeh and Fefferman, Bill and Marwaha, Kunal},
  title =	{{On the Power of Nonstandard Quantum Oracles}},
  booktitle =	{18th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2023)},
  pages =	{11:1--11:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-283-9},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{266},
  editor =	{Fawzi, Omar and Walter, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.TQC.2023.11},
  URN =		{urn:nbn:de:0030-drops-183215},
  doi =		{10.4230/LIPIcs.TQC.2023.11},
  annote =	{Keywords: quantum complexity, QCMA, expander graphs, representation theory}
}
Document
Track A: Algorithms, Complexity and Games
Quantum Algorithms and Lower Bounds for Linear Regression with Norm Constraints

Authors: Yanlin Chen and Ronald de Wolf

Published in: LIPIcs, Volume 261, 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)


Abstract
Lasso and Ridge are important minimization problems in machine learning and statistics. They are versions of linear regression with squared loss where the vector θ ∈ ℝ^d of coefficients is constrained in either 𝓁₁-norm (for Lasso) or in 𝓁₂-norm (for Ridge). We study the complexity of quantum algorithms for finding ε-minimizers for these minimization problems. We show that for Lasso we can get a quadratic quantum speedup in terms of d by speeding up the cost-per-iteration of the Frank-Wolfe algorithm, while for Ridge the best quantum algorithms are linear in d, as are the best classical algorithms. As a byproduct of our quantum lower bound for Lasso, we also prove the first classical lower bound for Lasso that is tight up to polylog-factors.

Cite as

Yanlin Chen and Ronald de Wolf. Quantum Algorithms and Lower Bounds for Linear Regression with Norm Constraints. In 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 261, pp. 38:1-38:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{chen_et_al:LIPIcs.ICALP.2023.38,
  author =	{Chen, Yanlin and de Wolf, Ronald},
  title =	{{Quantum Algorithms and Lower Bounds for Linear Regression with Norm Constraints}},
  booktitle =	{50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)},
  pages =	{38:1--38:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-278-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{261},
  editor =	{Etessami, Kousha and Feige, Uriel and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2023.38},
  URN =		{urn:nbn:de:0030-drops-180907},
  doi =		{10.4230/LIPIcs.ICALP.2023.38},
  annote =	{Keywords: Quantum algorithms, Regularized linear regression, Lasso, Ridge, Lower bounds}
}
Document
RANDOM
The Product of Gaussian Matrices Is Close to Gaussian

Authors: Yi Li and David P. Woodruff

Published in: LIPIcs, Volume 207, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2021)


Abstract
We study the distribution of the matrix product G₁ G₂ ⋯ G_r of r independent Gaussian matrices of various sizes, where G_i is d_{i-1} × d_i, and we denote p = d₀, q = d_r, and require d₁ = d_{r-1}. Here the entries in each G_i are standard normal random variables with mean 0 and variance 1. Such products arise in the study of wireless communication, dynamical systems, and quantum transport, among other places. We show that, provided each d_i, i = 1, …, r, satisfies d_i ≥ C p ⋅ q, where C ≥ C₀ for a constant C₀ > 0 depending on r, then the matrix product G₁ G₂ ⋯ G_r has variation distance at most δ to a p × q matrix G of i.i.d. standard normal random variables with mean 0 and variance ∏_{i = 1}^{r-1} d_i. Here δ → 0 as C → ∞. Moreover, we show a converse for constant r that if d_i < C' max{p,q}^{1/2}min{p,q}^{3/2} for some i, then this total variation distance is at least δ', for an absolute constant δ' > 0 depending on C' and r. This converse is best possible when p = Θ(q).

Cite as

Yi Li and David P. Woodruff. The Product of Gaussian Matrices Is Close to Gaussian. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 207, pp. 35:1-35:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{li_et_al:LIPIcs.APPROX/RANDOM.2021.35,
  author =	{Li, Yi and Woodruff, David P.},
  title =	{{The Product of Gaussian Matrices Is Close to Gaussian}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2021)},
  pages =	{35:1--35:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-207-5},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{207},
  editor =	{Wootters, Mary and Sanit\`{a}, Laura},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2021.35},
  URN =		{urn:nbn:de:0030-drops-147281},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2021.35},
  annote =	{Keywords: random matrix theory, total variation distance, matrix product}
}
Document
Random Sampling and Size Estimation Over Cyclic Joins

Authors: Yu Chen and Ke Yi

Published in: LIPIcs, Volume 155, 23rd International Conference on Database Theory (ICDT 2020)


Abstract
Computing joins is expensive, and often unnecessary when the output size is large. In 1999, Chaudhuri et al. [Surajit Chaudhuri et al., 1999] posed the problem of random sampling over joins as a potentially effective approach to avoiding computing the join in full, while obtaining important statistical information about the join results. Unfortunately, no significant progress has been made in the last 20 years, except for the case of acyclic joins. In this paper, we present the first non-trivial result on sampling over cyclic joins. We show that after a linear-time preprocessing step, a join result can be drawn uniformly at random in expected time O(IN^ρ/OUT), where IN^ρ is known as the AGM bound of the join and OUT is its output size. This result holds for all joins on binary relations, as well as certain joins on relations of higher arity. We further show how this algorithm immediately leads to a join size estimation algorithm with the same running time.

Cite as

Yu Chen and Ke Yi. Random Sampling and Size Estimation Over Cyclic Joins. In 23rd International Conference on Database Theory (ICDT 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 155, pp. 7:1-7:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{chen_et_al:LIPIcs.ICDT.2020.7,
  author =	{Chen, Yu and Yi, Ke},
  title =	{{Random Sampling and Size Estimation Over Cyclic Joins}},
  booktitle =	{23rd International Conference on Database Theory (ICDT 2020)},
  pages =	{7:1--7:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-139-9},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{155},
  editor =	{Lutz, Carsten and Jung, Jean Christoph},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2020.7},
  URN =		{urn:nbn:de:0030-drops-119315},
  doi =		{10.4230/LIPIcs.ICDT.2020.7},
  annote =	{Keywords: Random sampling, joins, join size estimation}
}
Document
A Tight Lower Bound for Entropy Flattening

Authors: Yi-Hsiu Chen, Mika Göös, Salil P. Vadhan, and Jiapeng Zhang

Published in: LIPIcs, Volume 102, 33rd Computational Complexity Conference (CCC 2018)


Abstract
We study entropy flattening: Given a circuit C_X implicitly describing an n-bit source X (namely, X is the output of C_X on a uniform random input), construct another circuit C_Y describing a source Y such that (1) source Y is nearly flat (uniform on its support), and (2) the Shannon entropy of Y is monotonically related to that of X. The standard solution is to have C_Y evaluate C_X altogether Theta(n^2) times on independent inputs and concatenate the results (correctness follows from the asymptotic equipartition property). In this paper, we show that this is optimal among black-box constructions: Any circuit C_Y for entropy flattening that repeatedly queries C_X as an oracle requires Omega(n^2) queries. Entropy flattening is a component used in the constructions of pseudorandom generators and other cryptographic primitives from one-way functions [Johan Håstad et al., 1999; John Rompel, 1990; Thomas Holenstein, 2006; Iftach Haitner et al., 2006; Iftach Haitner et al., 2009; Iftach Haitner et al., 2013; Iftach Haitner et al., 2010; Salil P. Vadhan and Colin Jia Zheng, 2012]. It is also used in reductions between problems complete for statistical zero-knowledge [Tatsuaki Okamoto, 2000; Amit Sahai and Salil P. Vadhan, 1997; Oded Goldreich et al., 1999; Vadhan, 1999]. The Theta(n^2) query complexity is often the main efficiency bottleneck. Our lower bound can be viewed as a step towards proving that the current best construction of pseudorandom generator from arbitrary one-way functions by Vadhan and Zheng (STOC 2012) has optimal efficiency.

Cite as

Yi-Hsiu Chen, Mika Göös, Salil P. Vadhan, and Jiapeng Zhang. A Tight Lower Bound for Entropy Flattening. In 33rd Computational Complexity Conference (CCC 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 102, pp. 23:1-23:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


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@InProceedings{chen_et_al:LIPIcs.CCC.2018.23,
  author =	{Chen, Yi-Hsiu and G\"{o}\"{o}s, Mika and Vadhan, Salil P. and Zhang, Jiapeng},
  title =	{{A Tight Lower Bound for Entropy Flattening}},
  booktitle =	{33rd Computational Complexity Conference (CCC 2018)},
  pages =	{23:1--23:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-069-9},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{102},
  editor =	{Servedio, Rocco A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2018.23},
  URN =		{urn:nbn:de:0030-drops-88669},
  doi =		{10.4230/LIPIcs.CCC.2018.23},
  annote =	{Keywords: Entropy, One-way function}
}
Document
An XML Framework for Integrating Continuous Queries, Composite Event Detection, and Database Condition Monitoring for Multiple Data Streams

Authors: Susan Urban, Suzanne Dietrich, and Yi Chen

Published in: Dagstuhl Seminar Proceedings, Volume 7191, Event Processing (2007)


Abstract
With advancements in technology over the last ten years, data management issues have evolved from a stored persistent form to also include streaming data generated from sensors and other software monitoring tools. Furthermore, distributed, event-based systems are becoming more prevalent, with a need to develop applications that can dynamically respond to information extracted from data streams. This research is investigating the integration of stream processing and event processing techniques, with expressive filtering capabilities that include queries over persistent databases to provide application context to the filtering process. Distributed Event Processing Agents (DEPAs) continuously filter events from multiple data streams of different formats that provide XML views. Composite events for data streams are expressed using the Composite Event Detection Language (CEDL) and mapped to Composite XQuery (CXQ) for implementation. CXQ is a language that extends XQuery with features from CEDL, including operators for expressing sequence, disjunction, conjunction, repetition, aggregation, and time windows for events. Continuous queries and composite event filters are integrated with techniques for materialized view maintenance and incremental evaluation in condition monitoring to provide efficient ways of enhancing stream filters with database queries. The filtering and event detection load is distributed among multiple DEPAs, with CXQ expressions decomposed to allocate subcomponents of the expression to DEPAs that efficiently communicate in the global detection of composite events. A unique aspect of our research is that it extends XQuery with temporal, composite event features to combine techniques for continuous queries in stream processing, incremental evaluation in condition monitoring, and detection and filtering of composite events, creating an expressive environment for the extraction of meaningful events from multiple data streams with XML views.

Cite as

Susan Urban, Suzanne Dietrich, and Yi Chen. An XML Framework for Integrating Continuous Queries, Composite Event Detection, and Database Condition Monitoring for Multiple Data Streams. In Event Processing. Dagstuhl Seminar Proceedings, Volume 7191, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)


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@InProceedings{urban_et_al:DagSemProc.07191.3,
  author =	{Urban, Susan and Dietrich, Suzanne and Chen, Yi},
  title =	{{An XML Framework for Integrating Continuous Queries, Composite Event Detection, and Database Condition Monitoring for Multiple Data Streams}},
  booktitle =	{Event Processing},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7191},
  editor =	{Mani Chandy and Opher Etzion and Rainer von Ammon},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.07191.3},
  URN =		{urn:nbn:de:0030-drops-11423},
  doi =		{10.4230/DagSemProc.07191.3},
  annote =	{Keywords: Composite events, stream processing, event filtering, extended XQuery, distributed event processing}
}
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