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We develop several new algorithms for learning Markov Decision Processes in an infinite-horizon average-reward setting with linear function approximation. Using the optimism principle and assuming that the MDP has a linear structure, we…

Machine Learning · Computer Science 2021-04-27 Chen-Yu Wei , Mehdi Jafarnia-Jahromi , Haipeng Luo , Rahul Jain

The Adwords and Online Bipartite Matching problems have enjoyed a renewed attention over the past decade due to their connection to Internet advertising. Our community has contributed, among other things, new models (notably stochastic) and…

Data Structures and Algorithms · Computer Science 2016-06-28 Yajun Wang , Sam Chiu-wai Wong

We provide new algorithms and conditional hardness for the problem of estimating effective resistances in $n$-node $m$-edge undirected, expander graphs. We provide an $\widetilde{O}(m\epsilon^{-1})$-time algorithm that produces with high…

Data Structures and Algorithms · Computer Science 2023-06-27 Rajat Vadiraj Dwaraknath , Ishani Karmarkar , Aaron Sidford

We study a classical iterative algorithm for balancing matrices in the $L_\infty$ norm via a scaling transformation. This algorithm, which goes back to Osborne and Parlett \& Reinsch in the 1960s, is implemented as a standard preconditioner…

Data Structures and Algorithms · Computer Science 2015-06-16 Leonard J. Schulman , Alistair Sinclair

We study the minimum weight basis problem on matroid when elements' weights are uncertain. For each element we only know a set of possible values (an uncertainty area) that contains its real weight. In some cases there exist bases that are…

Data Structures and Algorithms · Computer Science 2019-04-29 Arturo I. Merino , José A. Soto

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

We introduce the parametric matroid one-interdiction problem. Given a matroid, each element of its ground set is associated with a weight that depends linearly on a real parameter from a given parameter interval. The goal is to find, for…

Combinatorics · Mathematics 2024-08-15 Nils Hausbrandt , Oliver Bachtler , Stefan Ruzika , Luca E. Schäfer

In linear combinatorial optimization, we aim to find $S^* = \arg\min_{S \in \mathcal{F}} \langle w,\mathbf{1}_S \rangle$ for a family $\mathcal{F} \subseteq 2^U$ over a ground set $U$ of $n$ elements. Traditionally, $w$ is known or…

We consider a partial-feedback variant of the well-studied online PCA problem where a learner attempts to predict a sequence of $d$-dimensional vectors in terms of a quadratic loss, while only having limited feedback about the environment's…

Machine Learning · Computer Science 2019-02-11 Wojciech Kotłowski , Gergely Neu

Contention resolution schemes have proven to be an incredibly powerful concept which allows to tackle a broad class of problems. The framework has been initially designed to handle submodular optimization under various types of constraints,…

Data Structures and Algorithms · Computer Science 2018-11-27 Marek Adamczyk , Michał Włodarczyk

Matrix completion is the problem of recovering a low rank matrix by observing a small fraction of its entries. A series of recent works [KOM12,JNS13,HW14] have proposed fast non-convex optimization based iterative algorithms to solve this…

Numerical Analysis · Computer Science 2014-11-06 Prateek Jain , Praneeth Netrapalli

We study algorithmic matroid intersection coloring. Given $k$ matroids on a common ground set $U$ of $n$ elements, the goal is to partition $U$ into the fewest number of color classes, where each color class is independent in all matroids.…

Data Structures and Algorithms · Computer Science 2026-04-07 Stephen Arndt , Benjamin Moseley , Kirk Pruhs , Chaitanya Swamy , Michael Zlatin

In this paper, we study parallel algorithms for the correlation clustering problem, where every pair of two different entities is labeled with similar or dissimilar. The goal is to partition the entities into clusters to minimize the number…

Data Structures and Algorithms · Computer Science 2023-07-14 Nairen Cao , Shang-En Huang , Hsin-Hao Su

Maintaining a maximum bipartite matching online while minimizing recourse/augmentations is a well studied problem, motivated by content delivery, job scheduling, and hashing. A breakthrough result of Bernstein, Holm, and Rotenberg…

Data Structures and Algorithms · Computer Science 2023-09-20 Niv Buchbinder , Anupam Gupta , Daniel Hathcock , Anna R. Karlin , Sherry Sarkar

We present improved deterministic distributed algorithms for a number of well-studied matching problems, which are simpler, faster, more accurate, and/or more general than their known counterparts. The common denominator of these results is…

Data Structures and Algorithms · Computer Science 2017-08-08 Manuela Fischer

We obtain the first polynomial-time algorithm for exact tensor completion that improves over the bound implied by reduction to matrix completion. The algorithm recovers an unknown 3-tensor with $r$ incoherent, orthogonal components in…

Machine Learning · Computer Science 2017-06-27 Aaron Potechin , David Steurer

Asymptotically tight lower bounds are derived for the I/O complexity of a general class of hybrid algorithms computing the product of $n \times n$ square matrices combining ``\emph{Strassen-like}'' fast matrix multiplication approach with…

Data Structures and Algorithms · Computer Science 2019-04-30 Lorenzo De Stefani

We revisit the algorithmic problem of finding a triangle in a graph: We give a randomized combinatorial algorithm for triangle detection in a given $n$-vertex graph with $m$ edges running in $O(n^{7/3})$ time, or alternatively in…

Data Structures and Algorithms · Computer Science 2024-03-08 Adrian Dumitrescu

Let $P$ be an orthogonal polygon of $n$ vertices, without holes. The Orthogonal Polygon Covering with Squares (OPCS) problem takes as input such an orthogonal polygon $P$ with integral vertex coordinates, and asks to find the minimum number…

Computational Geometry · Computer Science 2024-11-19 Anubhav Dhar , Subham Ghosh , Sudeshna Kolay

We present a methodology for parallel acceleration of learning in the presence of matrix orthogonality and unitarity constraints of interest in several branches of machine learning. We show how an apparently sequential elementary rotation…

Machine Learning · Computer Science 2021-06-02 Firas Hamze