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We study the computation of doubly regularized Wasserstein barycenters, a recently introduced family of entropic barycenters governed by inner and outer regularization strengths. Previous research has demonstrated that various…

Optimization and Control · Mathematics 2023-07-26 Lénaïc Chizat , Tomas Vaškevičius

Intractable generative models are models for which the likelihood is unavailable but sampling is possible. Most approaches to parameter inference in this setting require the computation of some discrepancy between the data and the…

Computation · Statistics 2022-07-05 Ziang Niu , Johanna Meier , François-Xavier Briol

Recent work by Dhulipala et al. \cite{DLRSSY22} initiated the study of the $k$-core decomposition problem under differential privacy via a connection between low round/depth distributed/parallel graph algorithms and private algorithms with…

Data Structures and Algorithms · Computer Science 2024-03-01 Laxman Dhulipala , George Z. Li , Quanquan C. Liu

We study deterministic extractors for oblivious bit-fixing sources (a.k.a. resilient functions) and exposure-resilient functions with small min-entropy: of the function's n input bits, k << n bits are uniformly random and unknown to the…

Computational Complexity · Computer Science 2010-12-14 Yakir Reshef , Salil Vadhan

Classical nonlinear dimensionality reduction (NLDR) techniques like t-SNE, Isomap, and LLE excel at creating low-dimensional embeddings for data visualization but fundamentally lack the ability to map these embeddings back to the original…

Machine Learning · Computer Science 2025-10-16 Riddhish Thakare , Kingdom Mutala Akugri

We study pseudorandomness properties of permutations on $\{0,1\}^n$ computed by random circuits made from reversible $3$-bit gates (permutations on $\{0,1\}^3$). Our main result is that a random circuit of depth $n \cdot \tilde{O}(k^2)$,…

Computational Complexity · Computer Science 2025-02-13 William He , Ryan O'Donnell

Byte-Pair Encoding (BPE) has become a widely adopted subword tokenization method in modern language models due to its simplicity and strong empirical performance across downstream tasks. However, applying BPE to unsegmented languages such…

Computation and Language · Computer Science 2025-06-23 Yifan Hu , Frank Liang , Dachuan Zhao , Jonathan Geuter , Varshini Reddy , Craig W. Schmidt , Chris Tanner

Generative models trained with Differential Privacy (DP) are becoming increasingly prominent in the creation of synthetic data for downstream applications. Existing literature, however, primarily focuses on basic benchmarking datasets and…

Cryptography and Security · Computer Science 2024-02-08 Dingfan Chen , Marie Oestreich , Tejumade Afonja , Raouf Kerkouche , Matthias Becker , Mario Fritz

Maximum-distance-separable (MDS) codes are a class of erasure codes that are widely adopted to enhance the reliability of distributed storage systems (DSS). In (n, k) MDS coded DSS, the original data are stored into n distributed nodes in…

Information Theory · Computer Science 2017-06-16 Sheng Guan , Haibin Kan , Xin Wang

We show that Trevisan's extractor and its variants \cite{T99,RRV99} are secure against bounded quantum storage adversaries. One instantiation gives the first such extractor to achieve an output length $\Theta(K-b)$, where $K$ is the…

Quantum Physics · Physics 2010-03-31 Anindya De , Thomas Vidick

We study the NP-complete Minimum Shared Edges (MSE) problem. Given an undirected graph, a source and a sink vertex, and two integers p and k, the question is whether there are p paths in the graph connecting the source with the sink and…

Computational Complexity · Computer Science 2016-02-05 Till Fluschnik , Stefan Kratsch , Rolf Niedermeier , Manuel Sorge

In this letter, we propose a novel tensor-based modulation scheme for massive unsourced random access. The proposed modulation can be deemed as a summation of third-order tensors, of which the factors are representatives of subspaces. A…

Signal Processing · Electrical Eng. & Systems 2021-12-07 Zhenting Luan , Yuchi Wu , Shansuo Liang , Liping Zhang , Wei Han , Bo Bai

The recent proliferation of high-dimensional data, such as electronic health records and genetics data, offers new opportunities to find novel predictors of outcomes. Presented with a large set of candidate features, interest often lies in…

Methodology · Statistics 2024-09-24 Michael J. Martens , Anjishnu Banerjee , Xinran Qi , Yushu Shi

Random numbers are indispensable resources for application in modern science and technology. Therefore, a dedicate entropy source is essential, particularly cryptographic tasks and modern applications. In this work, we experimentally…

We investigate deterministic identification over arbitrary memoryless channels under the constraint that the error probabilities of first and second kind are exponentially small in the block length $\mathbf{n}$, controlled by reliability…

Information Theory · Computer Science 2025-07-29 Pau Colomer , Christian Deppe , Holger Boche , Andreas Winter

We introduce a systematic method for constructing polytope approximations to the quantum set in a variety of device-independent quantum random number generation (DI-QRNG) protocols. Our approach relies on two general-purpose algorithms that…

Quantum Physics · Physics 2026-03-11 Hyejung H. Jee , Florian J. Curchod , Mafalda L. Almeida

A unified framework to obtain all known lower bounds (random coding, typical random coding and expurgated bound) on the reliability function of a point-to-point discrete memoryless channel (DMC) is presented. By using a similar idea for a…

Information Theory · Computer Science 2010-10-08 Ali Nazari , Achilleas Anastasopoulos , S. Sandeep Pradhan

A linear-programming decoder for \emph{nonbinary} expander codes is presented. It is shown that the proposed decoder has the maximum-likelihood certificate properties. It is also shown that this decoder corrects any pattern of errors of a…

Information Theory · Computer Science 2016-11-17 Vitaly Skachek

How does one compile derivatives of tensor programs, such that the resulting code is purely functional (hence easier to optimize and parallelize) and provably efficient relative to the original program? We show that naively differentiating…

Programming Languages · Computer Science 2020-10-01 Gilbert Bernstein , Michael Mara , Tzu-Mao Li , Dougal Maclaurin , Jonathan Ragan-Kelley

Motivated by the desirability of universal composability, we analyze in terms of L_1 distinguishability the task of secret key generation from a joint random variable. Under this secrecy criterion, using the Renyi entropy of order 1+s for s…

Information Theory · Computer Science 2016-09-28 Masahito Hayashi
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