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A previous article shows that any linear height bounded normal proof of a tautology in the Natural Deduction for Minimal implicational logic $M_{\supset}$ is as huge as it is redundant. More precisely, any proof in a family of…

Computational Complexity · Computer Science 2021-01-26 Edward Hermann Haeusler

Diffusion language models (DLMs) have emerged as a promising alternative to the long-dominant autoregressive (AR) paradigm, offering a parallelable decoding process that could yield greater efficiency. Yet, in practice, current open-source…

Computation and Language · Computer Science 2025-11-11 Han Peng , Peiyu Liu , Zican Dong , Daixuan Cheng , Junyi Li , Yiru Tang , Shuo Wang , Wayne Xin Zhao

Regular resolution is a refinement of the resolution proof system requiring that no variable be resolved on more than once along any path in the proof. It is known that there exist sequences of formulas that require exponential-size proofs…

Logic in Computer Science · Computer Science 2024-02-27 Sam Buss , Emre Yolcu

We investigate a Linear-Quadratic-Gaussian (LQG) control and sensing co-design problem, where one jointly designs sensing and control policies. We focus on the realistic case where the sensing design is selected among a finite set of…

Optimization and Control · Mathematics 2020-05-20 Vasileios Tzoumas , Luca Carlone , George J. Pappas , Ali Jadbabaie

Sequential propositional logic deviates from ordinary propositional logic by taking into account that during the sequential evaluation of a propositional statement,atomic propositions may yield different Boolean values at repeated…

Logic in Computer Science · Computer Science 2011-06-28 J. A. Bergstra , A. Ponse

For substructural logics with contraction or weakening admitting cut-free sequent calculi, proof search was analyzed using well-quasi-orders on $\mathbb{N}^d$ (Dickson's lemma), yielding Ackermannian upper bounds via controlled bad-sequence…

Logic in Computer Science · Computer Science 2026-02-24 A. R. Balasubramanian , Vitor Greati , Revantha Ramanayake

We study optimal regret bounds for control in linear dynamical systems under adversarially changing strongly convex cost functions, given the knowledge of transition dynamics. This includes several well studied and fundamental frameworks…

Machine Learning · Computer Science 2019-09-12 Naman Agarwal , Elad Hazan , Karan Singh

We study derivative-free methods for policy optimization over the class of linear policies. We focus on characterizing the convergence rate of these methods when applied to linear-quadratic systems, and study various settings of driving…

Machine Learning · Computer Science 2020-05-19 Dhruv Malik , Ashwin Pananjady , Kush Bhatia , Koulik Khamaru , Peter L. Bartlett , Martin J. Wainwright

Typing of lambda-terms in Elementary and Light Affine Logic (EAL, LAL, resp.) has been studied for two different reasons: on the one hand the evaluation of typed terms using LAL (EAL, resp.) proof-nets admits a guaranteed polynomial…

Logic in Computer Science · Computer Science 2007-05-23 Patrick Baillot , Paolo Coppola , Ugo Dal Lago

This paper focuses on the expressive power of disjunctive and normal logic programs under the stable model semantics over finite, infinite, or arbitrary structures. A translation from disjunctive logic programs into normal logic programs is…

Artificial Intelligence · Computer Science 2013-04-03 Heng Zhang , Yan Zhang

This paper presents a property of propositional theories under the answer sets semantics (called Equilibrium Logic for this general syntax): any theory can always be reexpressed as a strongly equivalent disjunctive logic program, possibly…

Artificial Intelligence · Computer Science 2007-05-23 Pedro Cabalar , Paolo Ferraris

When an LLM-based agent improves on a task, is the gain from the model itself or from the reasoning paradigm wrapped around it? We study this question by comparing six inference-time paradigms, namely Direct, CoT, ReAct, Plan-Execute,…

This paper considers a quadratically-constrained cardinality minimization problem with applications to digital filter design, subset selection for linear regression, and portfolio selection. Two relaxations are investigated: the continuous…

Optimization and Control · Mathematics 2012-10-19 Dennis Wei

This paper develops a new technique for proving amortized, randomized cell-probe lower bounds on dynamic data structure problems. We introduce a new randomized nondeterministic four-party communication model that enables "accelerated",…

Data Structures and Algorithms · Computer Science 2016-04-12 Omri Weinstein , Huacheng Yu

Recovering underlying Directed Acyclic Graph (DAG) structures from observational data is highly challenging due to the combinatorial nature of the DAG-constrained optimization problem. Recently, DAG learning has been cast as a continuous…

Machine Learning · Computer Science 2022-12-23 Zhen Zhang , Ignavier Ng , Dong Gong , Yuhang Liu , Ehsan M Abbasnejad , Mingming Gong , Kun Zhang , Javen Qinfeng Shi

We study the current best model (KDG) for question answering on tabular data evaluated over the WikiTableQuestions dataset. Previous ablation studies performed against this model attributed the model's performance to certain aspects of its…

Machine Learning · Computer Science 2018-03-14 Pramod Kaushik Mudrakarta , Ankur Taly , Mukund Sundararajan , Kedar Dhamdhere

We prove super-polynomial lower bounds on the size of linear programming relaxations for approximation versions of constraint satisfaction problems. We show that for these problems, polynomial-sized linear programs are exactly as powerful…

Computational Complexity · Computer Science 2016-02-09 Siu On Chan , James R. Lee , Prasad Raghavendra , David Steurer

We propose upper and lower bounds on the maximum success probability for discriminating given quantum states. The proposed upper bound is obtained from a suboptimal solution to the dual problem of the corresponding optimal state…

Quantum Physics · Physics 2018-01-12 Kenji Nakahira , Tsuyoshi Sasaki Usuda , Kentaro Kato

Retrieval-Augmented Generation has shown remarkable results to address Large Language Models' hallucinations, which usually uses a large external corpus to supplement knowledge to LLMs. However, with the development of LLMs, the internal…

Computation and Language · Computer Science 2026-01-26 Qi Luo , Xiaonan Li , Junqi Dai , Shuang Cheng , Xipeng Qiu

We describe an algorithmic method of proof compression based on the introduction of Pi_2-cuts into a cut-free LK-proof. The current approach is based on an inversion of Gentzen s cut-elimination method and extends former methods for…

Logic in Computer Science · Computer Science 2018-01-16 Alexander Leitsch , Michael Peter Lettmann