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Food detection is becoming a fundamental task in food computing that supports various multimedia applications, including food recommendation and dietary monitoring. To deal with real-world scenarios, food detection needs to localize and…

Computer Vision and Pattern Recognition · Computer Science 2023-10-10 Pengfei Zhou , Weiqing Min , Yang Zhang , Jiajun Song , Ying Jin , Shuqiang Jiang

An efficient algorithm is developed that identifies all independencies implied by the topology of a Bayesian network. Its correctness and maximality stems from the soundness and completeness of d-separation with respect to probability…

Artificial Intelligence · Computer Science 2013-04-08 Dan Geiger , Tom S. Verma , Judea Pearl

We investigate the topological complexity of non Borel recognizable tree languages with regard to the difference hierarchy of analytic sets. We show that, for each integer $n \geq 1$, there is a $D_{\omega^n}({\bf \Sigma}^1_1)$-complete…

Logic · Mathematics 2009-11-05 Olivier Finkel , Pierre Simonnet

Pre-trained large language models (LLMs) need fine-tuning to improve their responsiveness to natural language instructions. Federated learning offers a way to fine-tune LLMs using the abundant data on end devices without compromising data…

Machine Learning · Computer Science 2024-05-28 Zhen Qin , Daoyuan Chen , Bingchen Qian , Bolin Ding , Yaliang Li , Shuiguang Deng

We study the selection of transfer languages for different Natural Language Processing tasks, specifically sentiment analysis, named entity recognition and dependency parsing. In order to select an optimal transfer language, we propose to…

Computation and Language · Computer Science 2023-02-01 Juuso Eronen , Michal Ptaszynski , Fumito Masui

In this paper, we presented a novel semi-supervised one-class classification algorithm which assumes that class is linearly separable from other elements. We proved theoretically that class is linearly separable if and only if it is maximal…

Machine Learning · Statistics 2017-05-03 Evgeny Bauman , Konstantin Bauman

Many complex multi-target prediction problems that concern large target spaces are characterised by a need for efficient prediction strategies that avoid the computation of predictions for all targets explicitly. Examples of such problems…

Information Retrieval · Computer Science 2018-03-06 Michiel Stock , Krzysztof Dembczynski , Bernard De Baets , Willem Waegeman

Instead of mining coherent topics from a given text corpus in a completely unsupervised manner, seed-guided topic discovery methods leverage user-provided seed words to extract distinctive and coherent topics so that the mined topics can…

Computation and Language · Computer Science 2023-01-12 Yu Zhang , Yunyi Zhang , Martin Michalski , Yucheng Jiang , Yu Meng , Jiawei Han

Kernel based methods provide a way to reconstruct potentially high-dimensional functions from meshfree samples, i.e., sampling points and corresponding target values. A crucial ingredient for this to be successful is the distribution of the…

Numerical Analysis · Mathematics 2021-05-19 Tizian Wenzel , Gabriele Santin , Bernard Haasdonk

A sliding window algorithm receives a stream of symbols and has to output at each time instant a certain value which only depends on the last $n$ symbols. If the algorithm is randomized, then at each time instant it produces an incorrect…

Formal Languages and Automata Theory · Computer Science 2018-02-22 Moses Ganardi , Danny Hucke , Markus Lohrey

Discovering latent topics from text corpora has been studied for decades. Many existing topic models adopt a fully unsupervised setting, and their discovered topics may not cater to users' particular interests due to their inability of…

Computation and Language · Computer Science 2025-02-19 Yu Zhang , Yu Meng , Xuan Wang , Sheng Wang , Jiawei Han

Decision trees are well-known due to their ease of interpretability. To improve accuracy, we need to grow deep trees or ensembles of trees. These are hard to interpret, offsetting their original benefits. Shapley values have recently become…

Machine Learning · Computer Science 2023-01-26 Peng Yu , Chao Xu , Albert Bifet , Jesse Read

Semantic Similarity between two sentences can be defined as a way to determine how related or unrelated two sentences are. The task of Semantic Similarity in terms of distributed representations can be thought to be generating sentence…

Computation and Language · Computer Science 2017-10-24 Richa Sharma , Muktabh Mayank Srivastava

In this paper, we study a series of algorithmic problems related to the subsequences occurring in the strings of a given language, under the assumption that this language is succinctly represented by a grammar generating it, or an automaton…

Formal Languages and Automata Theory · Computer Science 2024-10-11 Szilárd Zsolt Fazekas , Tore Koß , Florin Manea , Robert Mercaş , Timo Specht

A class of languages C is perfect if it is closed under Boolean operations and the emptiness problem is decidable. Perfect language classes are the basis for the automata-theoretic approach to model checking: a system is correct if the…

Formal Languages and Automata Theory · Computer Science 2012-08-28 Javier Esparza , Pierre Ganty , Rupak Majumdar

Morpho-syntactic lexicons provide information about the morphological and syntactic roles of words in a language. Such lexicons are not available for all languages and even when available, their coverage can be limited. We present a…

Computation and Language · Computer Science 2016-01-26 Manaal Faruqui , Ryan McDonald , Radu Soricut

When minimizing the empirical risk in binary classification, it is a common practice to replace the zero-one loss with a surrogate loss to make the learning objective feasible to optimize. Examples of well-known surrogate losses for binary…

Machine Learning · Statistics 2023-06-07 Nontawat Charoenphakdee , Jongyeong Lee , Masashi Sugiyama

The notion of the cover is a generalization of a period of a string, and there are linear time algorithms for finding the shortest cover. The seed is a more complicated generalization of periodicity, it is a cover of a superstring of a…

Context free languages allow one to express data with hierarchical structure, at the cost of losing some of the useful properties of languages recognized by finite automata on words. However, it is possible to restore some of these…

Formal Languages and Automata Theory · Computer Science 2015-11-03 Eryk Kopczynski

We study a well known noisy model of the graph isomorphism problem. In this model, the goal is to perfectly recover the vertex correspondence between two edge-correlated Erd\H{o}s-R\'{e}nyi random graphs, with an initial seed set of…

Machine Learning · Computer Science 2018-07-27 Elchanan Mossel , Jiaming Xu