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Deep learning models have achieved remarkable success in different areas of machine learning over the past decade; however, the size and complexity of these models make them difficult to understand. In an effort to make them more…

Computer Vision and Pattern Recognition · Computer Science 2022-06-20 Vikram V. Ramaswamy , Sunnie S. Y. Kim , Nicole Meister , Ruth Fong , Olga Russakovsky

Logic programs with ordered disjunction (LPODs) combine ideas underlying Qualitative Choice Logic (Brewka et al. KR 2002) and answer set programming. Logic programming under answer set semantics is extended with a new connective called…

Artificial Intelligence · Computer Science 2007-05-23 Gerhard Brewka

We consider an extension of the setting of label ranking, in which the learner is allowed to make predictions in the form of partial instead of total orders. Predictions of that kind are interpreted as a partial abstention: If the learner…

Artificial Intelligence · Computer Science 2011-12-05 Weiwei Cheng , Eyke Hüllermeier

Short-circuit evaluation denotes the semantics of propositional connectives in which the second argument is evaluated only if the first argument does not suffice to determine the value of the expression. In programming, short-circuit…

Logic in Computer Science · Computer Science 2022-03-18 Dalia Papuc , Alban Ponse

Embedding-based retrieval (EBR) methods are widely used in modern recommender systems thanks to its simplicity and effectiveness. However, along the journey of deploying and iterating on EBR in production, we still identify some fundamental…

Information Retrieval · Computer Science 2023-02-07 Yuan Zhang , Xue Dong , Weijie Ding , Biao Li , Peng Jiang , Kun Gai

The remarkable success of Artificial Intelligence in advancing automated decision-making is evident both in academia and industry. Within the plethora of applications, ranking systems hold significant importance in various domains. This…

Information Retrieval · Computer Science 2023-12-19 Alessandro Castelnovo , Riccardo Crupi , Nicolò Mombelli , Gabriele Nanino , Daniele Regoli

We present trichotomy results characterizing the complexity of reasoning with disjunctive logic programs. To this end, we introduce a certain definition schema for classes of programs based on a set of allowed arities of rules. We show that…

Logic in Computer Science · Computer Science 2014-10-08 Miroslaw Truszczynski

Disentangled representation has been widely explored in many fields due to its maximal compactness, interpretability and versatility. Recommendation system also needs disentanglement to make representation more explainable and general for…

Social and Information Networks · Computer Science 2020-10-27 Weiguang Chen , Wenjun Jiang , Xueqi Li , Kenli Li , Albert Zomaya , Guojun Wang

In recent years, multi-label classification problem has become a controversial issue. In this kind of classification, each sample is associated with a set of class labels. Ensemble approaches are supervised learning algorithms in which an…

Machine Learning · Computer Science 2018-01-09 Amirreza Mahdavi-Shahri , Mahboobeh Houshmand , Mahdi Yaghoobi , Mehrdad Jalali

We detail a procedure for the computation of the polynomial form of an electronic combinational circuit from the design equations in a truth table. The method uses the Buchberger algorithm rather than current traditional methods based on…

Hardware Architecture · Computer Science 2007-05-23 Germain Drolet

Interpretability is essential for machine learning algorithms in high-stakes application fields such as medical image analysis. However, high-performing black-box neural networks do not provide explanations for their predictions, which can…

Computer Vision and Pattern Recognition · Computer Science 2023-08-09 Susu Sun , Stefano Woerner , Andreas Maier , Lisa M. Koch , Christian F. Baumgartner

We classify programming languages according to evaluation order: each language fixes one evaluation order as the default, making it transparent to program in that evaluation order, and troublesome to program in the other. This paper…

Programming Languages · Computer Science 2020-08-25 Jana Dunfield

Consider a binary classification problem solved using a feed-forward artificial neural network (ANN). Let the ANN be composed of a ReLU layer and several linear layers (convolution, sum-pooling, or fully connected). We assume the network…

Logic in Computer Science · Computer Science 2024-08-27 Ingo Schmitt

In this paper, a new triangular decomposition algorithm is proposed for ordinary differential polynomial systems, which has triple exponential computational complexity. The key idea is to eliminate one algebraic variable from a set of…

Symbolic Computation · Computer Science 2015-03-17 Wei Zhu , Xiao-Shan Gao

We study a ranking and selection problem of learning from choice-based feedback with dynamic assortments. In this problem, a company sequentially displays a set of items to a population of customers and collects their choices as feedback.…

Machine Learning · Computer Science 2025-01-03 Junwen Yang , Yifan Feng

In this brief, we discuss the implementation of a third order semi-implicit differentiator as a complement of the recent work by the author that proposes an interconnected semi-implicit Euler double differentiators algorithm through Taylor…

Numerical Analysis · Mathematics 2024-08-02 Loïc Michel , Jean-Pierre Barbot

From a theoretical view, this paper addresses the general problem of designing ordinal classification methods based on comparing actions with subset of actions, which are representative of their classes (categories). The basic demand of the…

Theoretical Economics · Economics 2021-07-13 Eduardo Fernandez , Jorge Navarro , Efrain Solares

Using ultrafilter techniques we show that in any partition of $\mathbb{N}$ into 2 cells there is one cell containing infinitely many exponential triples, i.e. triples of the kind $a,b,a^b$ (with $a,b>1$). Also, we will show that any…

Combinatorics · Mathematics 2011-07-19 Alessandro Sisto

Evidential reasoning is cast as the problem of simplifying the evidence-hypothesis relation and constructing combination formulas that possess certain testable properties. Important classes of evidence as identifiers, annihilators, and…

Artificial Intelligence · Computer Science 2013-04-11 Yizong Cheng , Rangasami L. Kashyap

Aggregating conformal predictors is a standard way of balancing their predictive and computational efficiency while retaining their validity, at least approximately. An important advantage of conformal e-predictors is that they are easier…

Machine Learning · Computer Science 2026-05-11 Vladimir Vovk