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We investigate the proof complexity of a class of propositional formulas expressing a combinatorial principle known as the Kneser-Lov\'{a}sz Theorem. This is a family of propositional tautologies, indexed by an nonnegative integer parameter…

Computational Complexity · Computer Science 2018-05-16 Gabriel Istrate , Adrian Crăciun

In this paper we study MapReduce computations from a complexity-theoretic perspective. First, we formulate a uniform version of the MRC model of Karloff et al. (2010). We then show that the class of regular languages, and moreover all of…

Computational Complexity · Computer Science 2015-10-07 Benjamin Fish , Jeremy Kun , Ádám Dániel Lelkes , Lev Reyzin , György Turán

Despite their ubiquity in NLP tasks, Long Short-Term Memory (LSTM) networks suffer from computational inefficiencies caused by inherent unparallelizable recurrences, which further aggravates as LSTMs require more parameters for larger…

Computation and Language · Computer Science 2019-08-28 Genta Indra Winata , Andrea Madotto , Jamin Shin , Elham J. Barezi , Pascale Fung

We establish novel connections between magic in quantum circuits and communication complexity. In particular, we show that functions computable with low magic have low communication cost. Our first result shows that the $\mathsf{D}\|$…

Quantum Physics · Physics 2025-10-09 Uma Girish , Alex May , Natalie Parham , Henry Yuen

Let alpha = (a,b,...) be a composition. Consider the associated poset F(alpha), called a fence, whose covering relations are x_1 < x_2 < ... < x_{a+1} > x_{a+2} > ... > x_{a+b+1} < x_{a+b+2} < ... . We study the associated distributive…

Combinatorics · Mathematics 2020-09-01 Thomas McConville , Bruce E. Sagan , Clifford Smyth

Communication lower bounds have long been established for matrix multiplication algorithms. However, most methods of asymptotic analysis have either ignored the constant factors or not obtained the tightest possible values. Recent work has…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-05-27 Hussam Al Daas , Grey Ballard , Laura Grigori , Suraj Kumar , Kathryn Rouse

The low-rank matrix completion problem asks whether a given real matrix with missing values can be completed so that the resulting matrix has low rank or is close to a low-rank matrix. The completed matrix is often required to satisfy…

Computational Complexity · Computer Science 2025-06-24 Dror Chawin , Ishay Haviv

Weighted low-rank approximation (WLRA), a dimensionality reduction technique for data analysis, has been successfully used in several applications, such as in collaborative filtering to design recommender systems or in computer vision to…

Optimization and Control · Mathematics 2012-08-13 Nicolas Gillis , François Glineur

Reduced-rank regression estimates regression coefficients by imposing a low-rank constraint on the matrix of regression coefficients, thereby accounting for correlations among response variables. To further improve predictive accuracy and…

Methodology · Statistics 2026-01-14 Kanji Goto , Shintaro Yuki , Kensuke Tanioka , Hiroshi Yadohisa

The Shub-Smale Tau Conjecture is a hypothesis relating the number of integral roots of a polynomial f in one variable and the Straight-Line Program (SLP) complexity of f. A consequence of the truth of this conjecture is that, for the…

Number Theory · Mathematics 2007-05-23 J. Maurice Rojas

The inference of a large symmetric signal-matrix $\mathbf{S} \in \mathbb{R}^{N\times N}$ corrupted by additive Gaussian noise, is considered for two regimes of growth of the rank $M$ as a function of $N$. For sub-linear ranks…

Information Theory · Computer Science 2024-07-16 Farzad Pourkamali , Jean Barbier , Nicolas Macris

Based on the notion of maximal correlation, Kimeldorf, May and Sampson (1980) introduce a measure of correlation between two random variables, called the "concordant monotone correlation" (CMC). We revisit, generalize and prove new…

Information Theory · Computer Science 2016-06-23 Omid Etesami , Amin Gohari

Refinement Modal Logic (RML), which was recently introduced by Bozzelli et al., is an extension of classical modal logic which allows one to reason about a changing model. In this paper we study computational complexity questions related to…

Logic in Computer Science · Computer Science 2013-09-23 Antonis Achilleos , Michael Lampis

We initiate the study of the inherent tradeoffs between the size of a neural network and its robustness, as measured by its Lipschitz constant. We make a precise conjecture that, for any Lipschitz activation function and for most datasets,…

Machine Learning · Computer Science 2020-11-26 Sébastien Bubeck , Yuanzhi Li , Dheeraj Nagaraj

Let $(f,P)$ be an incentive compatible mechanism where $f$ is the social choice function and $P$ is the payment function. In many important settings, $f$ uniquely determines $P$ (up to a constant) and therefore a common approach is to focus…

Computer Science and Game Theory · Computer Science 2021-01-01 Shahar Dobzinski , Shiri Ron

We study infinite-horizon average-reward constrained Markov decision processes (CMDPs) under the weakly communicating assumption. Our contributions are twofold. First, we establish strong duality for weakly communicating average-reward…

Machine Learning · Computer Science 2026-05-13 Kihyun Yu , Beomhan Baek , Dabeen Lee

In this paper we turn the spotlight on a class of lexicographic ranking functions introduced by Bradley, Manna and Sipma in a seminal CAV 2005 paper, and establish for the first time the complexity of some problems involving the inference…

Programming Languages · Computer Science 2015-04-21 Amir M. Ben-Amram , Samir Genaim

In this note, we study the relation between the parity decision tree complexity of a boolean function $f$, denoted by $\mathrm{D}_{\oplus}(f)$, and the $k$-party number-in-hand multiparty communication complexity of the XOR functions…

Computational Complexity · Computer Science 2015-06-30 Penghui Yao

In this letter, we propose enhanced factored three way restricted Boltzmann machines (EFTW-RBMs) for speech detection. The proposed model incorporates conditional feature learning by multiplying the dynamical state of the third unit, which…

Sound · Computer Science 2017-04-24 Pengfei Sun , Jun Qin

Recently, large language models (LLMs) have advanced recommendation systems (RSs), and recent works have begun to explore how to integrate LLMs into industrial RSs. While most approaches deploy LLMs offline to generate and pre-cache…

Information Retrieval · Computer Science 2026-04-22 Yunjia Xi , Menghui Zhu , Jianghao Lin , Bo Chen , Ruiming Tang , Yong Yu , Weinan Zhang