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We give superpolynomial statistical query (SQ) lower bounds for learning two-hidden-layer ReLU networks with respect to Gaussian inputs in the standard (noise-free) model. No general SQ lower bounds were known for learning ReLU networks of…

Machine Learning · Computer Science 2022-11-15 Sitan Chen , Aravind Gollakota , Adam R. Klivans , Raghu Meka

Learning intersections of halfspaces is a central problem in Computational Learning Theory. Even for just two halfspaces, it remains a major open question whether learning is possible in polynomial time with respect to the margin $\gamma$…

Machine Learning · Computer Science 2025-11-18 Ilias Diakonikolas , Mingchen Ma , Lisheng Ren , Christos Tzamos

Subset-Sum and k-SAT are two of the most extensively studied problems in computer science, and conjectures about their hardness are among the cornerstones of fine-grained complexity. One of the most intriguing open problems in this area is…

Data Structures and Algorithms · Computer Science 2021-02-22 Amir Abboud , Karl Bringmann , Danny Hermelin , Dvir Shabtay

In this paper we focus on problems which do not admit a constant-factor approximation in polynomial time and explore how quickly their approximability improves as the allowed running time is gradually increased from polynomial to…

Data Structures and Algorithms · Computer Science 2015-02-23 Édouard Bonnet , Michael Lampis , Vangelis Th. Paschos

We prove a new structural lemma for partial Boolean functions $f$, which we call the seed lemma for DNF. Using the lemma, we give the first subexponential algorithm for proper learning of DNF in Angluin's Equivalence Query (EQ) model. The…

Machine Learning · Computer Science 2011-11-07 Lisa Hellerstein , Devorah Kletenik , Linda Sellie , Rocco Servedio

The study of optimal decision trees has gained increasing attention in recent years; however, despite substantial progress, it still suffers from two major challenges: First, trees constructed by existing optimal decision tree (ODT)…

Machine Learning · Computer Science 2026-05-04 Xi He

We present a comprehensive classical and parameterized complexity analysis of decision tree pruning operations, extending recent research on the complexity of learning small decision trees. Thereby, we offer new insights into the…

Machine Learning · Computer Science 2025-03-06 Juha Harviainen , Frank Sommer , Manuel Sorge , Stefan Szeider

Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, where optimality improves with increased computational time.…

Machine Learning · Statistics 2011-09-22 Christos Dimitrakakis

We obtain upper bounds, independent of the ambient dimension, for the number of realizable zero-nonzero patterns and (over ordered fields) sign conditions of a finite family of polynomials $\mathcal P$ restricted to an algebraic subset $V$…

Combinatorics · Mathematics 2026-01-05 Saugata Basu , Laxmi Parida

We prove that for every parity decision tree of depth $d$ on $n$ variables, the sum of absolute values of Fourier coefficients at level $\ell$ is at most $d^{\ell/2} \cdot O(\ell \cdot \log(n))^\ell$. Our result is nearly tight for small…

Computational Complexity · Computer Science 2021-05-14 Uma Girish , Avishay Tal , Kewen Wu

We study the problem of PAC learning one-hidden-layer ReLU networks with $k$ hidden units on $\mathbb{R}^d$ under Gaussian marginals in the presence of additive label noise. For the case of positive coefficients, we give the first…

Machine Learning · Computer Science 2020-06-23 Ilias Diakonikolas , Daniel M. Kane , Vasilis Kontonis , Nikos Zarifis

A decision tree recursively splits a feature space $\mathbb{R}^{d}$ and then assigns class labels based on the resulting partition. Decision trees have been part of the basic machine-learning toolkit for decades. A large body of work treats…

An upper dominating set is a minimal dominating set in a graph. In the \textsc{Upper Dominating Set} problem, the goal is to find an upper dominating set of maximum size. We study the complexity of parameterized algorithms for \textsc{Upper…

Data Structures and Algorithms · Computer Science 2021-01-20 Louis Dublois , Michael Lampis , Vangelis Th. Paschos

Decision tree learning is increasingly being used for pointwise inference. Important applications include causal heterogenous treatment effects and dynamic policy decisions, as well as conditional quantile regression and design of…

Machine Learning · Statistics 2024-02-08 Matias D. Cattaneo , Jason M. Klusowski , Peter M. Tian

The existence of a polynomial pivot rule for the simplex method for linear programming, policy iteration for Markov decision processes, and strategy improvement for parity games each are prominent open problems in their respective fields.…

Optimization and Control · Mathematics 2025-12-19 Yann Disser , Georg Loho , Matthew Maat , Nils Mosis

We prove a tight lower bound (up to constant factors) on the sample complexity of any non-interactive local differentially private protocol for optimizing a linear function over the simplex. This lower bound also implies a tight lower bound…

Cryptography and Security · Computer Science 2021-05-17 Jonathan Ullman

The problem of deciding the validity (QSAT) of quantified Boolean formulas (QBF) is a vivid research area in both theory and practice. In the field of parameterized algorithmics, the well-studied graph measure treewidth turned out to be a…

Computational Complexity · Computer Science 2020-07-06 Johannes Klaus Fichte , Markus Hecher , Andreas Pfandler

We show that every algorithm for testing $n$-variate Boolean functions for monotonicity must have query complexity $\tilde{\Omega}(n^{1/4})$. All previous lower bounds for this problem were designed for non-adaptive algorithms and, as a…

Computational Complexity · Computer Science 2015-11-17 Aleksandrs Belovs , Eric Blais

We introduce a method for proving lower bounds on the efficacy of semidefinite programming (SDP) relaxations for combinatorial problems. In particular, we show that the cut, TSP, and stable set polytopes on $n$-vertex graphs are not the…

Computational Complexity · Computer Science 2014-11-25 James R. Lee , Prasad Raghavendra , David Steurer

We prove superpolynomial length lower bounds for the semantic tree-like Frege refutation system with bounded line size. Concretely, for any function $n^{2-\varepsilon} \leq s(n) \leq 2^{n^{1-\varepsilon}}$ we exhibit an explicit family…

Computational Complexity · Computer Science 2026-05-01 Susanna F. de Rezende , David Engström , Yassine Ghannane , Kilian Risse