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The classical branch-and-bound algorithm for the integer feasibility problem has exponential worst case complexity. We prove that it is surprisingly efficient on reformulated problems, in which the columns of the constraint matrix are…

Optimization and Control · Mathematics 2009-08-06 Gabor Pataki , Mustafa Tural

With the increasing application of deep learning in mission-critical systems, there is a growing need to obtain formal guarantees about the behaviors of neural networks. Indeed, many approaches for verifying neural networks have been…

Machine Learning · Computer Science 2022-08-17 Tom Zelazny , Haoze Wu , Clark Barrett , Guy Katz

We use reproducing kernel methods to study various rigidity problems. The methods and setting allow us to also consider the non-positive case.

Complex Variables · Mathematics 2007-09-18 Daniel Alpay , Simeon Reich , David Shoikhet

The global Lipschitz constant of a neural network is related to robustness and generalization, yet unlike in many classical models, it is not plainly legible from the parameters. This has motivated sophisticated verification algorithms,…

Machine Learning · Computer Science 2026-05-11 Simon Kuang , Yuezhu Xu , S. Sivaranjani , Xinfan Lin

Motivated by the recent experimental demonstrations of quantum supremacy, proving the hardness of the output of random quantum circuits is an imperative near term goal. We prove under the complexity theoretical assumption of the…

Quantum Physics · Physics 2021-12-13 Yasuhiro Kondo , Ryuhei Mori , Ramis Movassagh

In this work, we prove upper and lower bounds over fields of positive characteristics for several fragments of the Ideal Proof System (IPS), an algebraic proof system introduced by Grochow and Pitassi (J. ACM 2018). Our results extend the…

Computational Complexity · Computer Science 2025-06-23 Amik Raj Behera , Nutan Limaye , Varun Ramanathan , Srikanth Srinivasan

We study the problem of constructing explicit families of matrices which cannot be expressed as a product of a few sparse matrices. In addition to being a natural mathematical question on its own, this problem appears in various…

Computational Complexity · Computer Science 2019-04-03 Mrinal Kumar , Ben Lee Volk

State-of-the-art classifiers have been shown to be largely vulnerable to adversarial perturbations. One of the most effective strategies to improve robustness is adversarial training. In this paper, we investigate the effect of adversarial…

Machine Learning · Computer Science 2018-11-27 Seyed-Mohsen Moosavi-Dezfooli , Alhussein Fawzi , Jonathan Uesato , Pascal Frossard

Deep neural networks have proven remarkably effective at solving many classification problems, but have been criticized recently for two major weaknesses: the reasons behind their predictions are uninterpretable, and the predictions…

Machine Learning · Computer Science 2017-11-28 Andrew Slavin Ross , Finale Doshi-Velez

We present a new method for proving lower bounds on quantum query algorithms. The new method is an extension of adversary method, by analyzing the eigenspace structure of the problem. Using the new method, we prove a strong direct product…

Quantum Physics · Physics 2007-05-23 Andris Ambainis

The quest for quantum computers is motivated by their potential for solving problems that defy existing, classical, computers. The theory of computational complexity, one of the crown jewels of computer science, provides a rigorous…

Statistical Mechanics · Physics 2010-09-10 C. R. Laumann , R. Moessner , A. Scardicchio , S. L. Sondhi

We investigate the complexity of the reachability problem for (deep) neural networks: does it compute valid output given some valid input? It was recently claimed that the problem is NP-complete for general neural networks and…

Computational Complexity · Computer Science 2026-04-08 Marco Sälzer , Martin Lange

We prove a query complexity lower bound for $\mathsf{QMA}$ protocols that solve approximate counting: estimating the size of a set given a membership oracle. This gives rise to an oracle $A$ such that $\mathsf{SBP}^A \not\subset…

Computational Complexity · Computer Science 2019-02-08 William Kretschmer

We consider the communication complexity of some fundamental convex optimization problems in the point-to-point (coordinator) and blackboard communication models. We strengthen known bounds for approximately solving linear regression,…

Data Structures and Algorithms · Computer Science 2024-03-29 Mehrdad Ghadiri , Yin Tat Lee , Swati Padmanabhan , William Swartworth , David Woodruff , Guanghao Ye

In this paper, we consider lower bounds on the query complexity for testing CSPs in the bounded-degree model. First, for any ``symmetric'' predicate $P:{0,1}^{k} \to {0,1}$ except \equ where $k\geq 3$, we show that every (randomized)…

Data Structures and Algorithms · Computer Science 2010-07-21 Yuichi Yoshida

Developing classification algorithms that are fair with respect to sensitive attributes of the data has become an important problem due to the growing deployment of classification algorithms in various social contexts. Several recent works…

Machine Learning · Computer Science 2020-04-16 L. Elisa Celis , Lingxiao Huang , Vijay Keswani , Nisheeth K. Vishnoi

Exploring the power of linear programming for combinatorial optimization problems has been recently receiving renewed attention after a series of breakthrough impossibility results. From an algorithmic perspective, the related questions…

Discrete Mathematics · Computer Science 2014-12-31 Stavros G. Kolliopoulos , Yannis Moysoglou

We initiate a program of parameterized proof complexity that aims to provide evidence that FPT is different from W[1]. A similar program already exists for the classes W[2] and W[SAT]. We contrast these programs and prove upper and lower…

Logic in Computer Science · Computer Science 2012-03-26 Barnaby Martin

We prove that for every odd $q\geq 3$, any $q$-query binary, possibly non-linear locally decodable code ($q$-LDC) $E:\{\pm1\}^k \rightarrow \{\pm1\}^n$ must satisfy $k \leq \tilde{O}(n^{1-2/q})$. For even $q$, this bound was established in…

Computational Complexity · Computer Science 2024-11-22 Arpon Basu , Jun-Ting Hsieh , Pravesh K. Kothari , Andrew D. Lin

This paper addresses the problem of formally verifying desirable properties of neural networks, i.e., obtaining provable guarantees that neural networks satisfy specifications relating their inputs and outputs (robustness to bounded norm…

Machine Learning · Computer Science 2018-08-06 Krishnamurthy , Dvijotham , Robert Stanforth , Sven Gowal , Timothy Mann , Pushmeet Kohli
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