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Code generation techniques generate code snippets automatically based on the problem requirements in natural language. Recently, large language models (LLMs) achieve the SOTA performance on code generation. However, LLMs still struggle at…

Software Engineering · Computer Science 2024-11-26 Jinhao Dong , Jun Sun , Wenjie Zhang , Jin Song Dong , Dan Hao

Linear regression models depend directly on the design matrix and its properties. Techniques that efficiently estimate model coefficients by partitioning rows of the design matrix are increasingly popular for large-scale problems because…

Machine Learning · Statistics 2019-07-23 Michael J. Kane , Bryan Lewis , Sekhar Tatikonda , Simon Urbanek

One requirement of maintaining digital information is storage. With the latest advances in the digital world, new emerging media types have required even more storage space to be kept than before. In fact, in many cases it is required to…

Data Structures and Algorithms · Computer Science 2025-01-22 Vasileios Alevizos , Nikitas Gerolimos , Sabrina Edralin , Clark Xu , Akebu Simasiku , Georgios Priniotakis , George Papakostas , Zongliang Yue

A distance-based inconsistency indicator, defined by the third author for the consistency-driven pairwise comparisons method, is extended to the incomplete case. The corresponding optimization problem is transformed into an equivalent…

Other Computer Science · Computer Science 2015-05-11 S. Bozoki , J. Fulop , W. W. Koczkodaj

The deployment of pre-trained perception models in novel environments often leads to performance degradation due to distributional shifts. Although recent artificial intelligence approaches for metacognition use logical rules to…

We consider here the problem of obtaining reliable, consistent information from inconsistent databases -- databases that do not have to satisfy given integrity constraints. We use the notion of consistent query answer -- a query answer…

Databases · Computer Science 2007-05-23 Jan Chomicki , Jerzy Marcinkowski

Large language models (LLMs) are being increasingly adopted in the software engineering domain, yet the robustness of their grasp on core software design concepts remains unclear. We conduct an empirical study to systematically evaluate…

Software Engineering · Computer Science 2025-12-30 Mootez Saad , Boqi Chen , José Antonio Hernández López , Dániel Varró , Tushar Sharma

We propose an SQP algorithm for mathematical programs with vanishing constraints which solves at each iteration a quadratic program with linear vanishing constraints. The algorithm is based on the newly developed concept of $\mathcal…

Optimization and Control · Mathematics 2016-11-28 Matúš Benko , Helmut Gfrerer

An uniform LP duality is an useful property of conic matrix systems. A consistent linear conic optimization problem yields uniform LP duality if for any linear cost function, for which the primal problem has finite optimal value, the…

Optimization and Control · Mathematics 2023-02-21 Kostyukova O. I. , Tchemisova T. , Dudina O. S

Linear constraints are the linear counterpart of Haskell's class constraints. Linearly typed parameters allow the programmer to control resources such as file handles and manually managed memory as linear arguments. Indeed, a linear type…

Programming Languages · Computer Science 2026-04-24 Arnaud Spiwack , Csongor Kiss , Jean-Philippe Bernardy , Nicolas Wu , Richard A. Eisenberg

A range of approaches have been proposed for estimating the accuracy or robustness of the measured performance of IR methods. One is to use bootstrapping of test sets, which, as we confirm, provides an estimate of variation in performance.…

Information Retrieval · Computer Science 2025-09-26 Meng Yuan , Justin Zobel

We propose a new exact approach for solving integer linear programming (ILP) problems which we will call projective splitting algorithms (PSAs). Unlike classical methods for solving ILP problems, PSAs conduct the search for the optimal…

Optimization and Control · Mathematics 2014-04-16 Federico Rodes , Isabel Mendez-Diaz , Paula Zabala

Large Reasoning Models (LRMs) have achieved remarkable success, yet they often suffer from producing unnecessary and verbose reasoning chains. We identify a core aspect of this issue as "invalid thinking" -- models tend to repeatedly…

Artificial Intelligence · Computer Science 2025-09-12 Zhengxiang Cheng , Dongping Chen , Mingyang Fu , Tianyi Zhou

For general quadratically-constrained quadratic programming (QCQP), we propose a parabolic relaxation described with convex quadratic constraints. An interesting property of the parabolic relaxation is that the original non-convex feasible…

Optimization and Control · Mathematics 2022-08-09 Ramtin Madani , Mersedeh Ashraphijuo , Mohsen Kheirandishfard , Alper Atamturk

Stochastic Constraint Programming (SCP) is an extension of Constraint Programming (CP) used for modelling and solving problems involving constraints and uncertainty. SCP inherits excellent modelling abilities and filtering algorithms from…

Artificial Intelligence · Computer Science 2017-04-25 Steven Prestwich , Roberto Rossi , Armagan Tarim

Iterative learning control (ILC) is a control strategy for repetitive tasks wherein information from previous runs is leveraged to improve future performance. Optimization-based ILC (OB-ILC) is a powerful design framework for constrained…

Systems and Control · Electrical Eng. & Systems 2022-05-27 Dominic Liao-McPherson , Efe C. Balta , Alisa Rupenyan , John Lygeros

Statistical sufficiency formalizes the notion of data reduction. In the decision theoretic interpretation, once a model is chosen all inferences should be based on a sufficient statistic. However, suppose we start with a set of procedures…

Statistics Theory · Mathematics 2018-08-01 Vincent Q. Vu

Large language models (LLMs) excel at zero-shot inference but continue to struggle with complex, multi-step reasoning. Recent methods that augment LLMs with intermediate reasoning steps such as Chain of Thought (CoT) and Program of Thought…

Computation and Language · Computer Science 2025-10-28 Adam Stein , Neelay Velingker , Mayur Naik , Eric Wong

A general asymptotic framework is developed for studying consis- tency properties of principal component analysis (PCA). Our frame- work includes several previously studied domains of asymptotics as special cases and allows one to…

Statistics Theory · Mathematics 2016-11-26 Dan Shen , Haipeng Shen , J. S. Marron

Partial label learning (PLL) learns from training examples each associated with multiple candidate labels, among which only one is valid. In recent years, benefiting from the strong capability of dealing with ambiguous supervision and the…

Artificial Intelligence · Computer Science 2024-02-28 Qian-Wei Wang , Bowen Zhao , Mingyan Zhu , Tianxiang Li , Zimo Liu , Shu-Tao Xia