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Data sketches are approximate succinct summaries of long streams. They are widely used for processing massive amounts of data and answering statistical queries about it in real-time. Existing libraries producing sketches are very fast, but…

Data Structures and Algorithms · Computer Science 2019-12-06 Arik Rinberg , Alexander Spiegelman , Edward Bortnikov , Eshcar Hillel , Idit Keidar , Lee Rhodes , Hadar Serviansky

We propose layer saturation - a simple, online-computable method for analyzing the information processing in neural networks. First, we show that a layer's output can be restricted to the eigenspace of its variance matrix without…

Machine Learning · Computer Science 2021-11-23 Mats L. Richter , Justin Shenk , Wolf Byttner , Anders Arpteg , Mikael Huss

Randomized sketching accelerates large-scale numerical linear algebra by reducing computational complexity. While the traditional sketch-and-solve approach reduces the problem size directly through sketching, the sketch-and-precondition…

Numerical Analysis · Mathematics 2025-05-23 Ruihan Xu , Yiping Lu

Maintaining legacy software requires many software and systems engineering hours. Assembly code programs, which demand low-level control over the computer machine state and have no variable names, are particularly difficult for humans to…

Software Engineering · Computer Science 2024-03-18 Celine Lee , Abdulrahman Mahmoud , Michal Kurek , Simone Campanoni , David Brooks , Stephen Chong , Gu-Yeon Wei , Alexander M. Rush

In this thesis we present several results in coding theory, concerning error-correcting codes and the Shannon capacity. 1. We give a general symmetry reduction of matrices occuring in semidefinite programs in coding theory. 2. We apply the…

Combinatorics · Mathematics 2020-05-07 Sven Polak

Speculative decoding and quantization effectively accelerate memory-bound inference of large language models. Speculative decoding mitigates the memory bandwidth bottleneck by verifying multiple tokens within a single forward pass, which…

Computation and Language · Computer Science 2025-05-30 Yudi Zhang , Weilin Zhao , Xu Han , Tiejun Zhao , Wang Xu , Hailong Cao , Conghui Zhu

In this paper we study the adaptivity of submodular maximization. Adaptivity quantifies the number of sequential rounds that an algorithm makes when function evaluations can be executed in parallel. Adaptivity is a fundamental concept that…

Data Structures and Algorithms · Computer Science 2018-04-18 Eric Balkanski , Aviad Rubinstein , Yaron Singer

SKETCHVERIFY is a within-tier cost-performance policy, not a universal accuracy improvement. The operational question: a practitioner stuck with a small, cheap code model (here, Gemini 3.1 Flash Lite) for latency, deployment, or budget…

Machine Learning · Computer Science 2026-05-12 Shan Jiang , Zijian Yi , Chenguang Zhu

Reducing the cognitive complexity of a piece of code to a given threshold is not trivial. Recently, we modeled software cognitive complexity reduction as an optimization problem and we proposed an approach to assist developers on this task.…

Software Engineering · Computer Science 2024-02-09 Rubén Saborido , Javier Ferrer , Francisco Chicano

Code editing constitutes a fundamental practice in software development, wherein developers modify existing codebases according to natural language requirements. Accurate code editing necessitates a comprehensive understanding of both the…

Software Engineering · Computer Science 2026-04-22 Chaozheng Wang , Zezhou Yang , Shuzheng Gao , Cuiyun Gao , Zongjie Li , Yichen Li , Ting Peng , Hailiang Huang , Yuetang Deng , Michael R. Lyu

Massive sizes of real-world graphs, such as social networks and web graph, impose serious challenges to process and perform analytics on them. These issues can be resolved by working on a small summary of the graph instead . A summary is a…

Data Structures and Algorithms · Computer Science 2018-06-12 Maham Anwar Beg , Muhammad Ahmad , Arif Zaman , Imdadullah Khan

We propose a new randomized algorithm for solving L2-regularized least-squares problems based on sketching. We consider two of the most popular random embeddings, namely, Gaussian embeddings and the Subsampled Randomized Hadamard Transform…

Machine Learning · Computer Science 2020-10-26 Jonathan Lacotte , Mert Pilanci

Sketching is widely used in randomized linear algebra for low-rank matrix approximation, column subset selection, and many other problems, and it has gained significant traction in machine learning applications. However, sketching large…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-24 Hussam Al Daas , Grey Ballard , Laura Grigori , Md Taufique Hussain , Suraj Kumar , Mohammad Marufur Rahman , Kathryn Rouse

Reasoning methods such as chain-of-thought prompting and self-consistency have shown immense potential to improve the accuracy of large language models across various reasoning tasks. However such methods involve generation of lengthy…

Computation and Language · Computer Science 2025-10-30 Disha Sheshanarayana , Tanishka Magar

Large language models have recently surpassed specialized systems on code generation, yet their effectiveness on other code-analysis tasks remains less clear. At the same time, multi-task learning offers a way to unify diverse objectives…

Software Engineering · Computer Science 2026-03-12 Amal Akli , Maxime Cordy , Mike Papadakis , Yves Le Traon

Recent algorithmic advances have made equality saturation an appealing approach to program optimization because it avoids the phase-ordering problem. Existing work uses external equality saturation libraries, or custom implementations that…

Programming Languages · Computer Science 2026-02-19 Jules Merckx , Alexandre Lopoukhine , Samuel Coward , Jianyi Cheng , Bjorn De Sutter , Tobias Grosser

Data sketches balance resource efficiency with controllable approximations for extracting features in high-volume, high-rate data. Two important points of interest are highlighted separately in recent works; namely, to (1) answer multiple…

Data Structures and Algorithms · Computer Science 2025-07-08 Martin Hilgendorf , Marina Papatriantafilou

Coded computing is a distributed paradigm that uses coding theory to introduce \textit{redundancy} and overcome bottlenecks in large-scale systems. In the same vein, randomized numerical linear algebra employs probabilistic methods to…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-19 Neophytos Charalambides , Arya Mazumdar

Large pre-trained language models have been used to generate code,providing a flexible interface for synthesizing programs from natural language specifications. However, they often violate syntactic and semantic rules of their output…

Machine Learning · Computer Science 2022-01-28 Gabriel Poesia , Oleksandr Polozov , Vu Le , Ashish Tiwari , Gustavo Soares , Christopher Meek , Sumit Gulwani

Query rewrite systems perform graph substitutions using rewrite rules to generate optimal SQL query plans. Rewriting logical and physical relational query plans is proven to be an NP-hard sequential decision-making problem with a search…

Databases · Computer Science 2024-07-19 George-Octavian Bărbulescu , Taiyi Wang , Zak Singh , Eiko Yoneki