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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

In this paper, we consider an adaptive approach to address optimization problems with uncertain cost parameters. Here, the decision maker selects an initial decision, observes the realization of the uncertain cost parameters, and then is…

Computational Complexity · Computer Science 2013-12-17 Ebrahim Nasrabadi , James B. Orlin

Lasso, or $\ell^1$ regularized least squares, has been explored extensively for its remarkable sparsity properties. It is shown in this paper that the solution to Lasso, in addition to its sparsity, has robustness properties: it is the…

Information Theory · Computer Science 2008-11-13 Huan Xu , Constantine Caramanis , Shie Mannor

Inverse Reinforcement Learning (IRL) aims to facilitate a learner's ability to imitate expert behavior by acquiring reward functions that explain the expert's decisions. Regularized IRL applies strongly convex regularizers to the learner's…

Machine Learning · Computer Science 2020-12-04 Wonseok Jeon , Chen-Yang Su , Paul Barde , Thang Doan , Derek Nowrouzezahrai , Joelle Pineau

We introduce a new symbolic representation based on an original generalization of counter abstraction. Unlike classical counter abstraction (used in the analysis of parameterized systems with unordered or unstructured topologies) the new…

Logic in Computer Science · Computer Science 2015-03-20 Ahmed Rezine

We present a natural, combinatorial problem whose solution is given by the meta-Fibonacci recurrence relation $a(n) = \sum_{i=1}^p a(n-i+1 - a(n-i))$, where $p$ is prime. This combinatorial problem is less general than those given in [3]…

Combinatorics · Mathematics 2019-02-11 Ramin Naimi , Eric Sundberg

Empirically, neural networks that attempt to learn programs from data have exhibited poor generalizability. Moreover, it has traditionally been difficult to reason about the behavior of these models beyond a certain level of input…

Machine Learning · Computer Science 2017-04-24 Jonathon Cai , Richard Shin , Dawn Song

Recent research has recognized interpretability and robustness as essential properties of trustworthy classification. Curiously, a connection between robustness and interpretability was empirically observed, but the theoretical reasoning…

Machine Learning · Computer Science 2021-02-16 Michal Moshkovitz , Yao-Yuan Yang , Kamalika Chaudhuri

Many results in mass partitions are proved by lifting $\mathbb{R}^d$ to a higher-dimensional space and dividing the higher-dimensional space into pieces. We extend such methods to use lifting arguments to polyhedral surfaces. Among other…

Combinatorics · Mathematics 2021-09-09 Pablo Soberón , Yuki Takahashi

Interpretability or explainability is an emerging research field in NLP. From a user-centric point of view, the goal is to build models that provide proper justification for their decisions, similar to those of humans, by requiring the…

We discuss the recently developed method of refined absorption and how it is used to provide a new proof of the Existence Conjecture for combinatorial designs. This method can also be applied to resolve open problems in extremal and…

Combinatorics · Mathematics 2025-10-24 Luke Postle

We consider the problem of computing the smallest possible distortion for embedding of a given n-point metric space into R^d, where d is fixed (and small). For d=1, it was known that approximating the minimum distortion with a factor better…

Computational Geometry · Computer Science 2009-09-29 Jiri Matousek , Anastasios Sidiropoulos

In this work we consider the primal mixed variational formulation of the Poisson equation with a line source. The analysis and approximation of this problem is non-standard as the line source causes the solutions to be singular. We start by…

Analysis of PDEs · Mathematics 2019-10-28 Ingeborg G. Gjerde , Kundan Kumar , Jan M. Nordbotten

We present and discuss a mixed conjunctive and disjunctive rule, a generalization of conflict repartition rules, and a combination of these two rules. In the belief functions theory one of the major problem is the conflict repartition…

Artificial Intelligence · Computer Science 2008-12-18 Arnaud Martin , Christophe Osswald

We consider the problem of recovering a signal consisting of a superposition of point sources from low-resolution data with a cut-off frequency f. If the distance between the sources is under 1/f, this problem is not well posed in the sense…

Optimization and Control · Mathematics 2016-09-09 Carlos Fernandez-Granda

In this paper a robust second-order method is developed for the solution of strongly convex l1-regularized problems. The main aim is to make the proposed method as inexpensive as possible, while even difficult problems can be efficiently…

Optimization and Control · Mathematics 2015-01-13 Kimon Fountoulakis , Jacek Gondzio

Reduced Rank Extrapolation (RRE) is a polynomial type method used to accelerate the convergence of sequences of vectors $\{\boldsymbol{x}_m\}$. It is applied successfully in different disciplines of science and engineering in the solution…

Numerical Analysis · Mathematics 2020-12-08 Avram Sidi

Phylogenetic reconciliation seeks to explain host-symbiont co-evolution by mapping parasite trees onto host trees through events such as cospeciation, duplication, host switching, and loss. Finding an optimal reconciliation that ensures…

Populations and Evolution · Quantitative Biology 2026-02-02 Cyriac Antony , Alessio Martino , Blerina Sinaimeri

The firefighter problem is NP-hard and admits a $(1-1/e)$ approximation based on rounding the canonical LP. In this paper, we first show a matching integrality gap of $(1-1/e+\epsilon)$ on the canonical LP. This result relies on a powerful…

Discrete Mathematics · Computer Science 2020-09-01 Parinya Chalermsook , Daniel Vaz

For sensitive problems, such as medical imaging or fraud detection, Neural Network (NN) adoption has been slow due to concerns about their reliability, leading to a number of algorithms for explaining their decisions. NNs have also been…

Machine Learning · Computer Science 2019-11-06 Walt Woods , Jack Chen , Christof Teuscher
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