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We study the problem of maximizing R{\'e}nyi entropy of order $2$ (equivalently, minimizing the index of coincidence) over the set of joint distributions with prescribed marginals. A closed-form optimizer is known under a feasibility…

Information Theory · Computer Science 2026-02-09 Pierre Jean-Claude Robert Bertrand

This paper develops a new technique for proving amortized, randomized cell-probe lower bounds on dynamic data structure problems. We introduce a new randomized nondeterministic four-party communication model that enables "accelerated",…

Data Structures and Algorithms · Computer Science 2016-04-12 Omri Weinstein , Huacheng Yu

A private compression design problem is studied, where an encoder observes useful data $Y$, wishes to compress it using variable length code and communicates it through an unsecured channel. Since $Y$ is correlated with private attribute…

Information Theory · Computer Science 2024-03-27 Amirreza Zamani , Tobias J. Oechtering , Deniz Gündüz , Mikael Skoglund

We present an iterative approach to constructing pseudorandom generators, based on the repeated application of mild pseudorandom restrictions. We use this template to construct pseudorandom generators for combinatorial rectangles and…

Computational Complexity · Computer Science 2012-10-02 Parikshit Gopalan , Raghu Meka , Omer Reingold , Luca Trevisan , Salil Vadhan

Various notions of non-malleable secret sharing schemes have been considered. In this paper, we review the existing work on non-malleable secret sharing and suggest a novel game-based definition. We provide a new construction of an…

Cryptography and Security · Computer Science 2023-05-17 Shannon Veitch , Douglas R. Stinson

Miller et al. \cite{MPVX15} devised a distributed\footnote{They actually showed a PRAM algorithm. The distributed algorithm with these properties is implicit in \cite{MPVX15}.} algorithm in the CONGEST model, that given a parameter $k =…

Data Structures and Algorithms · Computer Science 2017-02-07 Michael Elkin , Ofer Neiman

We introduce the Random Subsequence Model, a spin glass model on pairs of random strings $(X,Y) \in \{0,1\}^N \times \{0,1\}^M$ whose partition function counts subsequence embeddings of $Y$ into $X$. We study two variants: the null model,…

Information Theory · Computer Science 2026-04-09 Ryan Jeong , Francisco Pernice

We consider the isomorphism problem for groups specified by their multiplication tables. Until recently, the best published bound for the worst-case was achieved by the n^(log_p n + O(1)) generator-enumeration algorithm. In previous work…

Data Structures and Algorithms · Computer Science 2014-12-02 David J. Rosenbaum

We revisit the well-studied problem of estimating the Shannon entropy of a probability distribution, now given access to a probability-revealing conditional sampling oracle. In this model, the oracle takes as input the representation of a…

Cryptography and Security · Computer Science 2022-06-03 Priyanka Golia , Brendan Juba , Kuldeep S. Meel

We consider the secret key generation problem when sources are randomly excited by the sender and there is a noiseless public discussion channel. Our setting is thus similar to recent works on channels with action-dependent states where the…

Information Theory · Computer Science 2016-11-15 Tzu-Han Chou , Vincent Y. F. Tan , Stark C. Draper

Secure codes are widely-studied combinatorial structures which were introduced for traitor tracing in broadcast encryption. To determine the maximum size of such structures is the main research objective. In this paper, we investigate the…

Information Theory · Computer Science 2021-08-24 Bingchen Qian , Xin Wang , Gennian Ge

A curious property of randomized log-space search algorithms is that their outputs are often longer than their workspace. This leads to the question: how can we reproduce the results of a randomized log space computation without storing the…

Computational Complexity · Computer Science 2018-03-14 Ofer Grossman , Yang P. Liu

Maximum likelihood estimation of energy-based models is a challenging problem due to the intractability of the log-likelihood gradient. In this work, we propose learning both the energy function and an amortized approximate sampling…

Machine Learning · Computer Science 2019-05-29 Rithesh Kumar , Sherjil Ozair , Anirudh Goyal , Aaron Courville , Yoshua Bengio

Randomness extractors are algorithms that distill weak random sources into near-perfect random numbers. Two-source extractors enable this distillation process by combining two independent weak random sources. Raz's extractor (STOC '05) was…

Cryptography and Security · Computer Science 2025-06-19 Cameron Foreman , Lewis Wooltorton , Kevin Milner , Florian J. Curchod

In a seminal work, Nisan (Combinatorica'92) constructed a pseudorandom generator for length $n$ and width $w$ read-once branching programs with seed length $O(\log n\cdot \log(nw)+\log n\cdot\log(1/\varepsilon))$ and error $\varepsilon$. It…

Computational Complexity · Computer Science 2020-06-02 Eshan Chattopadhyay , Jyun-Jie Liao

In this paper, we set forth a new algorithm for generating approximately uniformly random spanning trees in undirected graphs. We show how to sample from a distribution that is within a multiplicative $(1+\delta)$ of uniform in expected…

Data Structures and Algorithms · Computer Science 2009-08-12 Jonathan A. Kelner , Aleksander Madry

The population protocol model is a computational model for passive mobile agents. We address the leader election problem, which determines a unique leader on arbitrary communication graphs starting from any configuration. Unfortunately,…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-10 Haruki Kanaya , Ryota Eguchi , Taisho Sasada , Michiko Inoue

This paper considers the \textit{minimum spanning tree (MST)} problem in the Congested Clique model and presents an algorithm that runs in $O(\log \log \log n)$ rounds, with high probability. Prior to this, the fastest MST algorithm in this…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-12-09 Sriram V. Pemmaraju , Vivek B. Sardeshmukh

Random subsampling of edges is a commonly employed technique in graph algorithms, underlying a vast array of modern algorithmic breakthroughs. Unfortunately, using this technique often leads to randomized algorithms with no clear path to…

Data Structures and Algorithms · Computer Science 2026-03-27 Aaron Putterman , Salil Vadhan , Vadim Zaripov

This paper studies the design of an optimal privacyaware estimator of a public random variable based on noisy measurements which contain private information. The public random variable carries non-private information, however, its estimate…

Optimization and Control · Mathematics 2018-08-08 Ehsan Nekouei , Henrik Sandberg , Mikael Skoglund , Karl H. Johansson
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