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$\alpha\mu$ is a search algorithm which repairs two defaults of Perfect Information Monte Carlo search: strategy fusion and non locality. In this paper we optimize $\alpha\mu$ for the game of Bridge, avoiding useless computations. The…

Artificial Intelligence · Computer Science 2021-02-01 Tristan Cazenave , Swann Legras , Véronique Ventos

We propose a new first-order optimisation algorithm to solve high-dimensional non-smooth composite minimisation problems. Typical examples of such problems have an objective that decomposes into a non-smooth empirical risk part and a…

Optimization and Control · Mathematics 2015-07-07 Niao He , Zaid Harchaoui

Quadratic Unconstrained Binary Optimization (QUBO) is a broad class of optimization problems with many practical applications. To solve its hard instances in an exact way, known classical algorithms require exponential time and several…

Quantum Physics · Physics 2021-01-21 Gian Giacomo Guerreschi

Semi-dual neural optimal transport learns a transport map via a max-min objective, yet training can converge to incorrect or degenerate maps. We fully characterize these spurious solutions in the common regime where data concentrate on…

Machine Learning · Computer Science 2026-02-05 Raymond Chu , Jaewoong Choi , Dohyun Kwon

Conditional lower bounds for dynamic graph problems has received a great deal of attention in recent years. While many results are now known for the fully-dynamic case and such bounds often imply worst-case bounds for the partially dynamic…

Data Structures and Algorithms · Computer Science 2016-05-04 Søren Dahlgaard

Since more than three decades, interior-point methods proved very useful for optimization, from linear over semidefinite to conic (and partly beyond non-convex) programming; despite the fact that already in the semidefinite case (even when…

Optimization and Control · Mathematics 2020-02-25 Konrad Schrempf

How many operations do we need on the average to compute an approximate root of a random Gaussian polynomial system? Beyond Smale's 17th problem that asked whether a polynomial bound is possible, we prove a quasi-optimal bound $\text{(input…

Numerical Analysis · Mathematics 2023-06-12 Pierre Lairez

In this paper, we give improved bounds for the computational complexity of computing with planar algebraic curves. More specifically, for arbitrary coprime polynomials $f$, $g \in \mathbb{Z}[x,y]$ and an arbitrary polynomial $h \in…

Symbolic Computation · Computer Science 2014-08-01 Alexander Kobel , Michael Sagraloff

Stochastic Multi-Objective Optimization (SMOO) is critical for decision-making trading off multiple potentially conflicting objectives in uncertain environments. SMOO aims at identifying the Pareto frontier, which contains all mutually…

Machine Learning · Computer Science 2026-04-02 Jinzhao Li , Nan Jiang , Yexiang Xue

We study dynamic $(1+\epsilon)$-approximation algorithms for the all-pairs shortest paths problem in unweighted undirected $n$-node $m$-edge graphs under edge deletions. The fastest algorithm for this problem is a randomized algorithm with…

Data Structures and Algorithms · Computer Science 2018-03-02 Monika Henzinger , Sebastian Krinninger , Danupon Nanongkai

We consider a general class of two-stage distributionally robust optimization (DRO) problems where the ambiguity set is constrained by fixed marginal probability laws that are not necessarily discrete. We derive primal and dual formulations…

Optimization and Control · Mathematics 2025-10-17 Ariel Neufeld , Qikun Xiang

We study the problem of global maximization of a function f given a finite number of evaluations perturbed by noise. We consider a very weak assumption on the function, namely that it is locally smooth (in some precise sense) with respect…

Machine Learning · Computer Science 2026-04-28 Michal Valko , Alexandra Carpentier , Rémi Munos

Second-order conic optimization (SOCO) can be considered as a special case of semidefinite optimization (SDO). In the literature it has been advised that a SOCO problem can be embedded in an SDO problem using the arrow-head matrix…

Optimization and Control · Mathematics 2023-01-31 Pouya Sampourmahani , Mohammadhossein Mohammadisiahroudi , Tamás Terlaky

Let $\A_0, \A_1, \ldots, \A_n$ be given square matrices of size $m$ with rational coefficients. The paper focuses on the exact computation of one point in each connected component of the real determinantal variety $\{\X \in\RR^n \: :\:…

Symbolic Computation · Computer Science 2014-12-19 Didier Henrion , Simone Naldi , Mohab Safey El Din

Hittmeir recently presented a deterministic algorithm that provably computes the prime factorisation of a positive integer $N$ in $N^{2/9+o(1)}$ bit operations. Prior to this breakthrough, the best known complexity bound for this problem…

Number Theory · Mathematics 2020-10-13 David Harvey

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 study a path-planning problem amid a set $\mathcal{O}$ of obstacles in $\mathbb{R}^2$, in which we wish to compute a short path between two points while also maintaining a high clearance from $\mathcal{O}$; the clearance of a point is…

Computational Geometry · Computer Science 2017-06-12 Pankaj K. Agarwal , Kyle Fox , Oren Salzman

We design an $n^{2+o(1)}$-time algorithm that constructs a cut-equivalent (Gomory-Hu) tree of a simple graph on $n$ nodes. This bound is almost-optimal in terms of $n$, and it improves on the recent $\tilde{O}(n^{2.5})$ bound by the authors…

Data Structures and Algorithms · Computer Science 2021-06-08 Amir Abboud , Robert Krauthgamer , Ohad Trabelsi

In this paper we construct quantum algorithms for matrix products over several algebraic structures called semirings, including the (max,min)-matrix product, the distance matrix product and the Boolean matrix product. In particular, we…

Quantum Physics · Physics 2021-10-05 François Le Gall , Harumichi Nishimura

Recovering nonlinearly degraded signal in the presence of noise is a challenging problem. In this work, this problem is tackled by minimizing the sum of a non convex least-squares fit criterion and a penalty term. We assume that the…

Signal Processing · Electrical Eng. & Systems 2019-02-27 Marc Castella , Jean-Christophe Pesquet , Arthur Marmin