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Parallel programmers face the often irreconcilable goals of programmability and performance. HPC systems use distributed memory for scalability, thereby sacrificing the programmability advantages of shared memory programming models.…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-01-21 Bharath Ramesh , Calvin J. Ribbens , Srinidhi Varadarajan

Motivated by group-project distribution, we introduce and study stable matching under the constraint of applicants needing to share a location to be matched with the same institute, which we call the Location-Restricted Stable Matching…

Data Structures and Algorithms · Computer Science 2025-08-05 Garret Castro

The verification of concurrent programs under weak-memory models is a burgeoning effort, owing to the increasing adoption of weak memory in concurrent software and hardware. Release/Acquire has become the standard model for high-performance…

Programming Languages · Computer Science 2026-04-16 Giovanna Kobus Conrado , Andreas Pavlogiannis

A central question in computer science and statistics is whether efficient algorithms can achieve the information-theoretic limits of statistical problems. Many computational-statistical tradeoffs have been shown under average-case…

Computational Complexity · Computer Science 2025-07-18 Guy Blanc , Caleb Koch , Carmen Strassle , Li-Yang Tan

Memory consistency models (MCMs) are at the heart of concurrent programming. They represent the behaviour of concurrent programs at the chip level. To test these models small program snippets called litmus test are generated, which show…

Programming Languages · Computer Science 2018-08-30 Ruth Hoffmann , Özgür Akgün , Susmit Sarkar

We find that the performance of state-of-the-art models on Natural Language Inference (NLI) and Reading Comprehension (RC) analysis/stress sets can be highly unstable. This raises three questions: (1) How will the instability affect the…

Computation and Language · Computer Science 2020-11-17 Xiang Zhou , Yixin Nie , Hao Tan , Mohit Bansal

We investigate the complexity of LTL learning, which consists in deciding given a finite set of positive ultimately periodic words, a finite set of negative ultimately periodic words, and a bound B given in unary, if there is an LTL-formula…

Logic in Computer Science · Computer Science 2023-12-19 Benjamin Bordais , Daniel Neider , Rajarshi Roy

We study the reachability problem for one-counter automata in which transitions can carry disequality tests. A disequality test is a guard that prohibits a specified counter value. This reachability problem has been known to be NP-hard and…

Formal Languages and Automata Theory · Computer Science 2024-08-23 Dmitry Chistikov , Jérôme Leroux , Henry Sinclair-Banks , Nicolas Waldburger

A tandem duplication denotes the process of inserting a copy of a segment of DNA adjacent to its original position. More formally, a tandem duplication can be thought of as an operation that converts a string $S = AXB$ into a string $T =…

Computational Complexity · Computer Science 2021-03-16 Ferdinando Cicalese , Nicolò Pilati

We present a thread-modular abstract interpretation(TMAI) technique to verify programs under the release-acquire (RA) memory model for safety property violations. The main contributions of our work are: we capture the execution order of…

Programming Languages · Computer Science 2021-08-19 Divyanjali Sharma , Subodh Sharma

Many natural combinatorial problems can be expressed as constraint satisfaction problems. This class of problems is known to be NP-complete in general, but certain restrictions on the form of the constraints can ensure tractability. The…

Computational Complexity · Computer Science 2020-10-05 Dmitriy Zhuk

We apply the replica analysis established by Gardner to the multi-constraint continuous knapsack problem,which is one of the linear programming problems and a most fundamental problem in the field of operations research (OR). For a large…

Disordered Systems and Neural Networks · Physics 2016-08-31 Jun-ichi Inoue

Although existing machine reading comprehension models are making rapid progress on many datasets, they are far from robust. In this paper, we propose an understanding-oriented machine reading comprehension model to address three kinds of…

Computation and Language · Computer Science 2022-07-04 Feiliang Ren , Yongkang Liu , Bochao Li , Shilei Liu , Bingchao Wang , Jiaqi Wang , Chunchao Liu , Qi Ma

Training a deep neural network (DNN) often involves stochastic optimization, which means each run will produce a different model. Several works suggest this variability is negligible when models have the same performance, which in the case…

Machine Learning · Statistics 2023-10-03 Sinjini Banerjee , Reilly Cannon , Tim Marrinan , Tony Chiang , Anand D. Sarwate

This work studies the (non)robustness of two-layer neural networks in various high-dimensional linearized regimes. We establish fundamental trade-offs between memorization and robustness, as measured by the Sobolev-seminorm of the model…

Machine Learning · Statistics 2021-06-07 Elvis Dohmatob

We explain that the difficulties of training deep neural networks come from a syndrome of three consistency issues. This paper describes our efforts in their analysis and treatment. The first issue is the training speed inconsistency in…

Machine Learning · Computer Science 2017-08-03 Chengxi Ye , Yezhou Yang , Cornelia Fermuller , Yiannis Aloimonos

This study investigates the learnability of Recurrent Neural Networks (RNNs) in classifying structured formal languages, focusing on counter and Dyck languages. Traditionally, both first-order (LSTM) and second-order (O2RNN) RNNs have been…

Computation and Language · Computer Science 2024-10-07 Neisarg Dave , Daniel Kifer , Lee Giles , Ankur Mali

The robustness to distribution changes ensures that NLP models can be successfully applied in the realistic world, especially for information extraction tasks. However, most prior evaluation benchmarks have been devoted to validating…

Computation and Language · Computer Science 2025-02-07 Ji Qi , Chuchun Zhang , Xiaozhi Wang , Kaisheng Zeng , Jifan Yu , Jinxin Liu , Jiuding Sun , Yuxiang Chen , Lei Hou , Juanzi Li , Bin Xu

We consider a bilevel continuous knapsack problem where the leader controls the capacity of the knapsack and the follower chooses an optimal packing according to his own profits, which may differ from those of the leader. To this bilevel…

Data Structures and Algorithms · Computer Science 2022-07-19 Christoph Buchheim , Dorothee Henke

Interpreting three-leaf binary trees or {\em rooted triples} as constraints yields an entailment relation, whereby binary trees satisfying some rooted triples must also thus satisfy others, and thence a closure operator, which is known to…

Data Structures and Algorithms · Computer Science 2018-07-03 Matthew P. Johnson
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