3 Search Results for "Mittal, Neeraj"


Document
Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning

Authors: Pritam Chandra, Ankit Garg, Neeraj Kayal, Kunal Mittal, and Tanmay Sinha

Published in: LIPIcs, Volume 287, 15th Innovations in Theoretical Computer Science Conference (ITCS 2024)


Abstract
We present a general framework for designing efficient algorithms for unsupervised learning problems, such as mixtures of Gaussians and subspace clustering. Our framework is based on a meta algorithm that learns arithmetic formulas in the presence of noise, using lower bounds. This builds upon the recent work of Garg, Kayal and Saha (FOCS '20), who designed such a framework for learning arithmetic formulas without any noise. A key ingredient of our meta algorithm is an efficient algorithm for a novel problem called Robust Vector Space Decomposition. We show that our meta algorithm works well when certain matrices have sufficiently large smallest non-zero singular values. We conjecture that this condition holds for smoothed instances of our problems, and thus our framework would yield efficient algorithms for these problems in the smoothed setting.

Cite as

Pritam Chandra, Ankit Garg, Neeraj Kayal, Kunal Mittal, and Tanmay Sinha. Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 287, pp. 25:1-25:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{chandra_et_al:LIPIcs.ITCS.2024.25,
  author =	{Chandra, Pritam and Garg, Ankit and Kayal, Neeraj and Mittal, Kunal and Sinha, Tanmay},
  title =	{{Learning Arithmetic Formulas in the Presence of Noise: A General Framework and Applications to Unsupervised Learning}},
  booktitle =	{15th Innovations in Theoretical Computer Science Conference (ITCS 2024)},
  pages =	{25:1--25:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-309-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{287},
  editor =	{Guruswami, Venkatesan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2024.25},
  URN =		{urn:nbn:de:0030-drops-195537},
  doi =		{10.4230/LIPIcs.ITCS.2024.25},
  annote =	{Keywords: Arithmetic Circuits, Robust Vector Space Decomposition, Subspace Clustering, Mixtures of Gaussians}
}
Document
Modular Recoverable Mutual Exclusion Under System-Wide Failures

Authors: Sahil Dhoked, Wojciech Golab, and Neeraj Mittal

Published in: LIPIcs, Volume 281, 37th International Symposium on Distributed Computing (DISC 2023)


Abstract
Recoverable mutual exclusion (RME) is a fault-tolerant variation of Dijkstra’s classic mutual exclusion (ME) problem that allows processes to fail by crashing as long as they recover eventually. A growing body of literature on this topic, starting with the problem formulation by Golab and Ramaraju (PODC'16), examines the cost of solving the RME problem, which is quantified by counting the expensive shared memory operations called remote memory references (RMRs), under a variety of conditions. Published results show that the RMR complexity of RME algorithms, among other factors, depends crucially on the failure model used: individual process versus system-wide. Recent work by Golab and Hendler (PODC'18) also suggests that explicit failure detection can be helpful in attaining constant RMR solutions to the RME problem in the system-wide failure model. Follow-up work by Jayanti, Jayanti, and Joshi (SPAA'23) shows that such a solution exists even without employing a failure detector, albeit this solution uses a more complex algorithmic approach. In this work, we dive deeper into the study of RMR-optimal RME algorithms for the system-wide failure model, and present contributions along multiple directions. First, we introduce the notion of withdrawing from a lock acquisition rather than resetting the lock. We use this notion to design a withdrawable RME algorithm with optimal O(1) RMR complexity for both cache-coherent (CC) and distributed shared memory (DSM) models in a modular way without using an explicit failure detector. In some sense, our technique marries the simplicity of Golab and Hendler’s algorithm with Jayanti, Jayanti and Joshi’s weaker system model. Second, we present a variation of our algorithm that supports fully dynamic process participation (i.e., both joining and leaving) in the CC model, while maintaining its constant RMR complexity. We show experimentally that our algorithm is substantially faster than Jayanti, Jayanti, and Joshi’s algorithm despite having stronger correctness properties. Finally, we establish an impossibility result for fully dynamic RME algorithms with bounded RMR complexity in the DSM model that are adaptive with respect to space, and provide a wait-free withdraw section.

Cite as

Sahil Dhoked, Wojciech Golab, and Neeraj Mittal. Modular Recoverable Mutual Exclusion Under System-Wide Failures. In 37th International Symposium on Distributed Computing (DISC 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 281, pp. 17:1-17:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{dhoked_et_al:LIPIcs.DISC.2023.17,
  author =	{Dhoked, Sahil and Golab, Wojciech and Mittal, Neeraj},
  title =	{{Modular Recoverable Mutual Exclusion Under System-Wide Failures}},
  booktitle =	{37th International Symposium on Distributed Computing (DISC 2023)},
  pages =	{17:1--17:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-301-0},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{281},
  editor =	{Oshman, Rotem},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2023.17},
  URN =		{urn:nbn:de:0030-drops-191431},
  doi =		{10.4230/LIPIcs.DISC.2023.17},
  annote =	{Keywords: mutual exclusion, shared memory, persistent memory, fault tolerance, system-wide failure, RMR complexity, dynamic joining, dynamic leaving}
}
Document
Brief Announcement
Brief Announcement: Fast and Scalable Group Mutual Exclusion

Authors: Shreyas Gokhale and Neeraj Mittal

Published in: LIPIcs, Volume 121, 32nd International Symposium on Distributed Computing (DISC 2018)


Abstract
The group mutual exclusion (GME) problem is a generalization of the classical mutual exclusion problem in which every critical section is associated with a type or session. Critical sections belonging to the same session can execute concurrently, whereas critical sections belonging to different sessions must be executed serially. The well-known read-write mutual exclusion problem is a special case of the group mutual exclusion problem. In a shared memory system, locks based on traditional mutual exclusion or its variants are commonly used to manage contention among processes. In concurrent algorithms based on fine-grained synchronization, a single lock is used to protect access to a small number of shared objects (e.g., a lock for every tree node) so as to minimize contention window. Evidently, a large number of shared objects in the system would translate into a large number of locks. Also, when fine-grained synchronization is used, most lock accesses are expected to be uncontended in practice. Most existing algorithms for the solving the GME problem have high space-complexity per lock. Further, all algorithms except for one have high step-complexity in the uncontented case. This makes them unsuitable for use in concurrent algorithms based on fine-grained synchronization. In this work, we present a novel GME algorithm for an asynchronous shared-memory system that has O(1) space-complexity per GME lock when the system contains a large number of GME locks as well as O(1) step-complexity when the system contains no conflicting requests.

Cite as

Shreyas Gokhale and Neeraj Mittal. Brief Announcement: Fast and Scalable Group Mutual Exclusion. In 32nd International Symposium on Distributed Computing (DISC 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 121, pp. 49:1-49:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


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@InProceedings{gokhale_et_al:LIPIcs.DISC.2018.49,
  author =	{Gokhale, Shreyas and Mittal, Neeraj},
  title =	{{Brief Announcement: Fast and Scalable Group Mutual Exclusion}},
  booktitle =	{32nd International Symposium on Distributed Computing (DISC 2018)},
  pages =	{49:1--49:3},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-092-7},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{121},
  editor =	{Schmid, Ulrich and Widder, Josef},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2018.49},
  URN =		{urn:nbn:de:0030-drops-98381},
  doi =		{10.4230/LIPIcs.DISC.2018.49},
  annote =	{Keywords: Group Mutual Exclusion, Fine-Grained Synchronization, Space Complexity, Contention-Free Step Complexity}
}
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