arXiv Machine Learning

How (and when) can you fit examples to logic-based hypothesis classes over infinite structures?

arXiv:2606. 01107v1 Announce Type: cross Abstract: We study fitting problems, sometimes called ``training problems'', where we have a finite sample consisting of inputs and outputs, and we want to know whether there is a function in a certain class that could produce these outputs, exactly or approximately, on the given inputs.

arXiv AI
Jul 24

Representative Sets in Propositional Abduction

arXiv:2607. 21183v1 Announce Type: cross Abstract: The propositional abduction problem is a well-known form of non-monotonic reasoning where we are asked to find an explanation of a given manifestation.

By Johannes Schmidt (J\"onk\"oping University), Mohamed Maizia (J\"onk\"oping University, Link\"oping University), Victor Lagerkvist (Link\"oping University), Johannes K. Fichte (Link\"oping University)
arXiv Machine Learning
Jul 9

Is Randomness Necessary for Adaptive Data Analysis?

arXiv:2607. 07085v1 Announce Type: cross Abstract: The Adaptive Data Analysis (ADA) problem formalizes the challenge of preventing false discovery and overfitting when a dataset is repeatedly reused.

By Edith Cohen, Haim Kaplan, Yishay Mansour, Shay Sapir, Uri Stemmer
arXiv AI
Jun 11

The Power of Test-Time Training for Approximate Sampling

arXiv:2606. 11437v1 Announce Type: cross Abstract: Efficiently sampling from a complex probability distribution is a fundamental problem which has become increasingly pertinent in recent years with the rise of generative AI, as sophisticated sampling procedures from LLMs have been proposed to solve challenging reasoning problems.

By Noah Golowich, Ankur Moitra, Dhruv Rohatgi
Hugging Face Trending Papers
Aug 3

Optimal Unambiguous DNFs and Alon-Saks-Seymour

We construct unambiguous DNFs having width $O(n)$ but $0$-certificate complexity $Ω(n^2)$. By utilizing the special structure of these DNFs, we prove a lifting theorem with a constant-sized gadget that lifts the DNF to a communication problem, while losslessly translating the separation in certificate complexity to a separation in communication complexity.

arXiv AI
Jul 28

Answering Path Queries under Linear and Guarded Existential Rules

arXiv:2607. 22636v1 Announce Type: new Abstract: Ontology-mediated query answering is concerned with the problem of answering queries over knowledge bases consisting of a database instance and an ontology.

By Jean-Fran\c{c}ois Baget (LIRMM, Inria, University of Montpellier, CNRS, France), Meghyn Bienvenu (Univ. Bordeaux, CNRS, Bordeaux INP, LaBRI, France), Marie-Laure Mugnier (LIRMM, Inria, University of Montpellier, CNRS, France), Micha\"el Thomazo (Inria, DIENS, ENS, PSL University, CNRS, France)
arXiv Machine Learning
Jul 20

Testing Distributions Against Bounded Distinguishers

arXiv:2607. 15645v1 Announce Type: cross Abstract: Motivated by the challenge of testing distributions over high-dimensional or continuous domains, we study distribution testing with respect to bounded classes of distinguishers.

By Mark Bun, Rathin Desai, Renato Ferreira Pinto Jr