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We present a unifying framework for generating extended formulations for the polyhedral outer approximations used in algorithms for mixed-integer convex programming (MICP). Extended formulations lead to fewer iterations of outer…

Optimization and Control · Mathematics 2016-06-02 Miles Lubin , Emre Yamangil , Russell Bent , Juan Pablo Vielma

Computational complexity characterizes the usage of spatial and temporal resources by computational processes. In the classical theory of computation, e.g. in the Turing Machine model, computational processes employ only local space and…

Quantum Physics · Physics 2025-09-25 Chris Fields , James F. Glazebrook , Antonino Marciano , Emanuele Zappala

Simulating interactions between non-spherical colloidal particles is computationally challenging due to the complex dependency of forces and energies on their geometry. We introduce and evaluate both descriptor-based and end-to-end models…

Soft Condensed Matter · Physics 2025-09-22 B. Rusen Argun , Antonia Statt

Formally verifying the correctness of mathematical proofs is more accessible than ever, however, the learning curve remains steep for many of the state-of-the-art interactive theorem provers (ITP). Deriving the most appropriate subsequent…

Logic in Computer Science · Computer Science 2024-11-05 Liao Zhang , David M. Cerna , Cezary Kaliszyk

Neural models combining representation learning and reasoning in an end-to-end trainable manner are receiving increasing interest. However, their use is severely limited by their computational complexity, which renders them unusable on real…

Artificial Intelligence · Computer Science 2018-07-24 Pasquale Minervini , Matko Bosnjak , Tim Rocktäschel , Sebastian Riedel

Neural symbolic processing aims to combine the generalization of logical learning approaches and the performance of neural networks. The Neural Theorem Proving (NTP) model by Rocktaschel et al (2017) learns embeddings for concepts and…

Machine Learning · Computer Science 2019-06-18 Michiel de Jong , Fei Sha

In the evaluation of treatment effects, it is of major policy interest to know if the treatment is beneficial for some and harmful for others, a phenomenon known as qualitative interaction. We formulate this question as a multiple testing…

Methodology · Statistics 2017-08-29 Qingyuan Zhao , Dylan S. Small , Weijie Su

We present a proof system for establishing the correctness of results produced by optimization algorithms, with a focus on mixed-integer programming (MIP). Our system generalizes the seminal work of Bogaerts, Gocht, McCreesh, and…

Optimization and Control · Mathematics 2023-11-09 Jasper van Doornmalen , Leon Eifler , Ambros Gleixner , Christopher Hojny

Neural Theorem Proving (NTP) employs LLMs to automate formal proofs in proof assistants. While LLMs have achieved relatively remarkable success in informal reasoning tasks using natural languages, the transition to mechanized formal theorem…

Programming Languages · Computer Science 2025-12-24 Qiyuan Xu , Renxi Wang , Peixin Wang , Haonan Li , Conrad Watt

Quantum samplers are believed capable of sampling efficiently from distributions that are classically hard to sample from. We consider a sampler inspired by the classical Ising model. It is nonadaptive and therefore experimentally amenable.…

Quantum Physics · Physics 2019-07-17 Theodoros Kapourniotis , Animesh Datta

We provide a general framework to remove short advice by formulating the following computational task for a function $f$: given two oracles at least one of which is honest (i.e. correctly computes $f$ on all inputs) as well as an input, the…

Computational Complexity · Computer Science 2015-04-08 Shuichi Hirahara

Model-based Reinforcement Learning (RL) is a popular learning paradigm due to its potential sample efficiency compared to model-free RL. However, existing empirical model-based RL approaches lack the ability to explore. This work studies a…

Machine Learning · Computer Science 2021-07-16 Yuda Song , Wen Sun

The LCF tradition of interactive theorem proving, which was started by Milner in the 1970-ies, appears to be tied to the classic READ-EVAL-PRINT-LOOP of sequential and synchronous evaluation of prover commands. We break up this loop and…

Logic in Computer Science · Computer Science 2013-07-09 Makarius Wenzel

Mixed integer convex and nonlinear programs, MICP and MINLP, are expressive but require long solving times. Recent work that combines data-driven methods on solver heuristics has shown potential to overcome this issue allowing for…

Optimization and Control · Mathematics 2022-08-30 Xuan Lin , Gabriel I. Fernandez , Dennis W. Hong

The study of interactive proofs in the context of distributed network computing is a novel topic, recently introduced by Kol, Oshman, and Saxena [PODC 2018]. In the spirit of sequential interactive proofs theory, we study the power of…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-12 Pierluigi Crescenzi , Pierre Fraigniaud , Ami Paz

Bell-inequality violations establish that two systems share some quantum entanglement. We give a simple test to certify that two systems share an asymptotically large amount of entanglement, n EPR states. The test is efficient: unlike…

Quantum Physics · Physics 2018-09-06 Rui Chao , Ben W. Reichardt , Chris Sutherland , Thomas Vidick

Mixed-integer programming (MIP) research is both mathematically sophisticated and engineering-intensive: testing an algorithmic hypothesis within a branch-and-cut solver requires substantial implementation, debugging, tuning, and…

Artificial Intelligence · Computer Science 2026-05-12 Liding Xu , Yugeng Zhou , Sebastian Pokutta

The class of languages having polynomial-time classical or quantum interactive proof systems ($\mathsf{IP}$ or $\mathsf{QIP}$, respectively) is identical to $\mathsf{PSPACE}$. We show that $\mathsf{PSPACE}$ (and so $\mathsf{QIP}$) is subset…

Quantum Physics · Physics 2025-08-29 Abuzer Yakaryılmaz

World-class human players have been outperformed in a number of complex two person games (Go, Chess, Checkers) by Deep Reinforcement Learning systems. However, owing to tractability considerations minimax regret of a learning system cannot…

Artificial Intelligence · Computer Science 2019-02-27 Céline Hocquette , Stephen H. Muggleton

We approach the 3-SAT satisfiability problem with the quantum-inspired method of imaginary time propagation (ITP) applied to matrix product states (MPS) on a classical computer. This ansatz is fundamentally limited by a quantum entanglement…

Quantum Physics · Physics 2026-03-09 Tim Pokart , Frank Pollmann , Jan Carl Budich