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We introduce a method for analyzing the complexity of natural language processing tasks, and for predicting the difficulty new NLP tasks. Our complexity measures are derived from the Kolmogorov complexity of a class of automata --- {\it…

cmp-lg · Computer Science 2016-08-31 Wlodek Zadrozny

To refactor already working code while keeping reliability, compatibility and perhaps security, we can borrow ideas from micropass/nanopass compilers. By treating the procedure of software refactoring as composing code transformations, and…

Software Engineering · Computer Science 2023-08-15 Yu Liu

The notion of bounded expansion captures uniform sparsity of graph classes and renders various algorithmic problems that are hard in general tractable. In particular, the model-checking problem for first-order logic is fixed-parameter…

In this paper we provide a detailed analysis of the iteration complexity of dual first order methods for solving conic convex problems. When it is difficult to project on the primal feasible set described by convex constraints, we use the…

Optimization and Control · Mathematics 2015-03-16 Ion Necoara , Andrei Patrascu

We analyze the bit complexity of efficient algorithms for fundamental optimization problems, such as linear regression, $p$-norm regression, and linear programming (LP). State-of-the-art algorithms are iterative, and in terms of the number…

Data Structures and Algorithms · Computer Science 2023-04-06 Mehrdad Ghadiri , Richard Peng , Santosh S. Vempala

We introduce a novel approach to the automated termination analysis of computer programs: we use neural networks to represent ranking functions. Ranking functions map program states to values that are bounded from below and decrease as a…

Machine Learning · Computer Science 2022-09-07 Mirco Giacobbe , Daniel Kroening , Julian Parsert

Fast Fourier Transform (FFT) is an efficient algorithm to compute the Discrete Fourier Transform (DFT) and its inverse. In this paper, we pay special attention to the description of complex-data FFT. We analyze two common descriptions of…

Numerical Analysis · Computer Science 2011-10-28 Zhengjun Cao , Xiao Fan

Modern processors deploy a variety of weak memory models, which for efficiency reasons may (appear to) execute instructions in an order different to that specified by the program text. The consequences of instruction reordering can be…

Programming Languages · Computer Science 2018-12-04 Robert J. Colvin , Graeme Smith

The field of computational complexity is concerned both with the intrinsic hardness of computational problems and with the efficiency of algorithms to solve them. Given such a problem, normally one designs an algorithm to solve it and sets…

Computational Complexity · Computer Science 2017-11-13 Fabiano de S. Oliveira , Valmir C. Barbosa

Fully automatic worst-case complexity analysis has a number of applications in computer-assisted program manipulation. A classical and powerful approach to complexity analysis consists in formally deriving, from the program syntax, a set of…

Mathematical Software · Computer Science 2007-05-23 Roberto Bagnara , Andrea Pescetti , Alessandro Zaccagnini , Enea Zaffanella

We perform a refined complexity-theoretic analysis of three classical problems in the context of Hierarchical Task Network Planning: the verification of a provided plan, whether an executable plan exists, and whether a given state can be…

Computational Complexity · Computer Science 2025-01-23 Cornelius Brand , Robert Ganian , Fionn Mc Inerney , Simon Wietheger

Several methods have been proposed for classifying long textual documents using Transformers. However, there is a lack of consensus on a benchmark to enable a fair comparison among different approaches. In this paper, we provide a…

Computation and Language · Computer Science 2022-03-23 Hyunji Hayley Park , Yogarshi Vyas , Kashif Shah

Recent research in mechanistic interpretability has attempted to reverse-engineer Transformer models by carefully inspecting network weights and activations. However, these approaches require considerable manual effort and still fall short…

Machine Learning · Computer Science 2023-11-01 Dan Friedman , Alexander Wettig , Danqi Chen

Constructor rewriting systems are said to be cons-free if, roughly, constructor terms in the right-hand sides of rules are subterms of the left-hand sides; the computational intuition is that rules cannot build new data structures. In…

Computational Complexity · Computer Science 2023-06-22 Cynthia Kop , Jakob Grue Simonsen

Verification of higher-order probabilistic programs is a challenging problem. We present a verification method that supports several quantitative properties of higher-order probabilistic programs. Usually, extending verification methods to…

Logic in Computer Science · Computer Science 2024-07-04 Satoshi Kura , Hiroshi Unno

Scientists often use observational time series data to study complex natural processes, but regression analyses often assume simplistic dynamics. Recent advances in deep learning have yielded startling improvements to the performance of…

Machine Learning · Computer Science 2023-04-21 Cory Shain , William Schuler

Higher-order constructs extend the expressiveness of first-order (Constraint) Logic Programming ((C)LP) both syntactically and semantically. At the same time assertions have been in use for some time in (C)LP systems helping programmers…

Programming Languages · Computer Science 2014-04-17 Nataliia Stulova , José F. Morales , Manuel V. Hermenegildo

We set up a parametrised monadic translation for a class of call-by-value functional languages, and prove a corresponding soundness theorem. We then present a series of concrete instantiations of our translation, demonstrating that a number…

Logic in Computer Science · Computer Science 2023-06-22 Thomas Powell

Fundamentally, every static program analyser searches for a proof through a combination of heuristics providing candidate solutions and a candidate validation technique. Essentially, the heuristic reduces a second-order problem to a…

Logic in Computer Science · Computer Science 2015-01-20 Cristina David , Daniel Kroening , Matt Lewis

Predicting the runtime complexity of a programming code is an arduous task. In fact, even for humans, it requires a subtle analysis and comprehensive knowledge of algorithms to predict time complexity with high fidelity, given any code. As…

Machine Learning · Computer Science 2019-11-05 Jagriti Sikka , Kushal Satya , Yaman Kumar , Shagun Uppal , Rajiv Ratn Shah , Roger Zimmermann