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In 2009, Roeglin and Teng showed that the smoothed number of Pareto optimal solutions of linear multi-criteria optimization problems is polynomially bounded in the number $n$ of variables and the maximum density $\phi$ of the semi-random…

Data Structures and Algorithms · Computer Science 2015-03-17 Tobias Brunsch , Heiko Roeglin

We consider an instance of the following problem: Parties P_1,..., P_k each receive an input x_i, and a coordinator (distinct from each of these parties) wishes to compute f(x_1,..., x_k) for some predicate f. We are interested in one-round…

Computational Complexity · Computer Science 2013-01-22 Daniel Apon , Jonathan Katz , Alex J. Malozemoff

In this work, we introduce an online model for communication complexity. Analogous to how online algorithms receive their input piece-by-piece, our model presents one of the players, Bob, his input piece-by-piece, and has the players Alice…

Data Structures and Algorithms · Computer Science 2017-11-16 Josh Alman , Joshua R. Wang , Huacheng Yu

The log-rank conjecture in communication complexity suggests that the deterministic communication complexity of any Boolean rank-r function is bounded by polylog(r). Recently, major progress was made by Lovett who proved that the…

Computational Complexity · Computer Science 2014-09-24 Thomas Rothvoss

In this paper we present a rudimentary model for low-latency anonymous communication systems. Specifically, we study distributed OR algorithm as an abstract of the system. Based on our model, we give several satisfactory lower bounds of…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-06 Yufan Zheng

We design and analyze new protocols to verify the correctness of various computations on matrices over the ring F[x] of univariate polynomials over a field F. For the sake of efficiency, and because many of the properties we verify are…

Symbolic Computation · Computer Science 2019-12-12 David Lucas , Vincent Neiger , Clément Pernet , Daniel S. Roche , Johan Rosenkilde

Discrete diffusion has recently emerged as a promising paradigm in discrete data modeling. However, existing methods typically rely on a fixed rate transition matrix during training, which not only limits the expressiveness of latent…

Machine Learning · Computer Science 2025-05-27 Hengli Li , Yuxuan Wang , Song-Chun Zhu , Ying Nian Wu , Zilong Zheng

We develop lower bounds on communication in the memory hierarchy or between processors for nested bilinear algorithms, such as Strassen's algorithm for matrix multiplication. We build on a previous framework that establishes communication…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-09-29 Caleb Ju , Yifan Zhang , Edgar Solomonik

In this paper, we develop a new communication model to prove a data structure lower bound for the dynamic interval union problem. The problem is to maintain a multiset of intervals $\mathcal{I}$ over $[0, n]$ with integer coordinates,…

Data Structures and Algorithms · Computer Science 2015-12-07 Huacheng Yu

This paper studies the one-way communication complexity of the subgroup membership problem, a classical problem closely related to basic questions in quantum computing. Here Alice receives, as input, a subgroup $H$ of a finite group $G$;…

Computational Complexity · Computer Science 2021-10-05 Scott Aaronson , François Le Gall , Alexander Russell , Seiichiro Tani

We investigate the randomized and quantum communication complexities of the well-studied Equality function with small error probability $\epsilon$, getting optimal constant factors in the leading terms in a number of different models. In…

Quantum Physics · Physics 2023-10-19 Olivier Lalonde , Nikhil S. Mande , Ronald de Wolf

The classical Perceptron algorithm of Rosenblatt can be used to find a linear threshold function to correctly classify $n$ linearly separable data points, assuming the classes are separated by some margin $\gamma > 0$. A foundational result…

Machine Learning · Computer Science 2022-10-19 Guanghui Wang , Rafael Hanashiro , Etash Guha , Jacob Abernethy

The communication matrix for two-way deterministic finite automata (2DFA) with $n$ states is defined for an automaton over a full alphabet of all $(2n+1)^n$ possible symbols: its rows and columns are indexed by strings, and the entry $(u,…

Formal Languages and Automata Theory · Computer Science 2023-12-12 Semyon Petrov , Fedor Petrov , Alexander Okhotin

Weighted low rank approximation (WLRA) is an important yet computationally challenging primitive with applications ranging from statistical analysis, model compression, and signal processing. To cope with the NP-hardness of this problem,…

Data Structures and Algorithms · Computer Science 2024-06-05 David P. Woodruff , Taisuke Yasuda

We derive fundamental lower bounds on the performance of optical metrology and communication systems in a Bayesian framework. The derivation uses classical rate-distortion theory in conjunction with bounds on the capacity to transmit…

Quantum Physics · Physics 2018-09-24 Ranjith Nair

We study the symmetric weighted first-order model counting task and present ApproxWFOMC, a novel anytime method for efficiently bounding the weighted first-order model count in the presence of an unweighted first-order model counting…

Artificial Intelligence · Computer Science 2020-01-16 Timothy van Bremen , Ondrej Kuzelka

We exhibit an $n$-bit partial function with randomized communication complexity $O(\log n)$ but such that any completion of this function into a total one requires randomized communication complexity $n^{\Omega(1)}$. In particular, this…

Computational Complexity · Computer Science 2025-11-10 Mika Göös , Nathaniel Harms , Artur Riazanov , Anastasia Sofronova , Dmitry Sokolov , Weiqiang Yuan

String matching is the problem of deciding whether a given $n$-bit string contains a given $k$-bit pattern. We study the complexity of this problem in three settings. Communication complexity. For small $k$, we provide near-optimal upper…

Computational Complexity · Computer Science 2019-02-21 Alexander Golovnev , Mika Göös , Daniel Reichman , Igor Shinkar

Estimates of the approximate factor model are increasingly used in empirical work. Their theoretical properties, studied some twenty years ago, also laid the ground work for analysis on large dimensional panel data models with cross-section…

Econometrics · Economics 2020-08-04 Jushan Bai , Serena Ng

We study the problem of learning a structured approximation (low-rank, sparse, banded, etc.) to an unknown matrix $A$ given access to matrix-vector product (matvec) queries of the form $x \rightarrow Ax$ and $x \rightarrow A^Tx$. This…

Data Structures and Algorithms · Computer Science 2025-07-28 Noah Amsel , Pratyush Avi , Tyler Chen , Feyza Duman Keles , Chinmay Hegde , Cameron Musco , Christopher Musco , David Persson