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This article concerns a class of generalized linear mixed models for clustered data, where the random effects are mapped uniquely onto the grouping structure and are independent between groups. We derive necessary and sufficient conditions…

Methodology · Statistics 2017-09-20 Jarod Y. L. Lee , Peter J. Green , Louise M. Ryan

Asymptotic properties of finitely generated subgroups of free groups, and of finite group presentations, can be considered in several fashions, depending on the way these objects are represented and on the distribution assumed on these…

Group Theory · Mathematics 2018-04-25 Frédérique Bassino , Cyril Nicaud , Pascal Weil

Despite recent advances, goal-directed generation of structured discrete data remains challenging. For problems such as program synthesis (generating source code) and materials design (generating molecules), finding examples which satisfy…

Machine Learning · Computer Science 2020-10-26 Amina Mollaysa , Brooks Paige , Alexandros Kalousis

It is well-known that typical word embedding methods such as Word2Vec and GloVe have the property that the meaning can be composed by adding up the embeddings (additive compositionality). Several theories have been proposed to explain…

Computation and Language · Computer Science 2022-12-20 Masahiro Naito , Sho Yokoi , Geewook Kim , Hidetoshi Shimodaira

Though there are some works on improving distributed word representations using lexicons, the improper overfitting of the words that have multiple meanings is a remaining issue deteriorating the learning when lexicons are used, which needs…

Computation and Language · Computer Science 2017-03-10 Yuanzhi Ke , Masafumi Hagiwara

In this paper we show the distributions of sliding block patterns for Bernoulli processes with finite alphabet, which is not based on the induction on sample size. We show a new inclusion-exclusion formula in multivariate generating…

Information Theory · Computer Science 2019-02-13 Hayato Takahashi

Large language models (LLMs) are powerful tools that have found applications beyond human-machine interfaces and chatbots. In particular, their ability to generate reasoning traces motivated their use in many prediction tasks like math…

Computation and Language · Computer Science 2026-03-03 Ayoub Hammal , Pierre Zweigenbaum , Caio Corro

The analysis of strings of $n$ random variables with geometric distribution has recently attracted renewed interest: Archibald et al. consider the number of distinct adjacent pairs in geometrically distributed words. They obtain the…

Probability · Mathematics 2024-02-14 Guy Louchard , Werner Schachinger , Mark Daniel Ward

We explore recently introduced definition modeling technique that provided the tool for evaluation of different distributed vector representations of words through modeling dictionary definitions of words. In this work, we study the problem…

Computation and Language · Computer Science 2018-06-27 Artyom Gadetsky , Ilya Yakubovskiy , Dmitry Vetrov

Compounding is a highly productive word-formation process in some languages that is often problematic for natural language processing applications. In this paper, we investigate whether distributional semantics in the form of word…

Computation and Language · Computer Science 2015-09-16 Joachim Daiber , Lautaro Quiroz , Roger Wechsler , Stella Frank

Recent neural sequence-to-sequence models with a copy mechanism have achieved remarkable progress in various text generation tasks. These models addressed out-of-vocabulary problems and facilitated the generation of rare words. However, the…

Computation and Language · Computer Science 2021-12-21 Sanghyuk Choi , Jeong-in Hwang , Hyungjong Noh , Yeonsoo Lee

Grammar development environments (GDE's) for analysis and for generation have not yet come together. Despite the fact that analysis-oriented GDE's (such as ALEP) may include some possibility of sentence generation, the development…

cmp-lg · Computer Science 2007-05-23 John A. Bateman

We introduce two different approaches for clustering semantically similar words. We accommodate ambiguity by allowing a word to belong to several clusters. Both methods use a graph-theoretic representation of words and their paradigmatic…

Other Condensed Matter · Physics 2009-09-29 Beate Dorow , Dominic Widdows , Katarina Ling , Jean-Pierre Eckmann , Danilo Sergi , Elisha Moses

We study supervised learning problems using clustering constraints to impose structure on either features or samples, seeking to help both prediction and interpretation. The problem of clustering features arises naturally in text…

Machine Learning · Computer Science 2016-09-20 Vincent Roulet , Fajwel Fogel , Alexandre d'Aspremont , Francis Bach

To overcome the computational bottleneck of various data perturbation procedures such as the bootstrap and cross validations, we propose the Generative Multiple-purpose Sampler (GMS), which constructs a generator function to produce…

Methodology · Statistics 2023-10-18 Minsuk Shin , Shijie Wang , Jun S Liu

Current state-of-the-art nonparametric Bayesian text clustering methods model documents through multinomial distribution on bags of words. Although these methods can effectively utilize the word burstiness representation of documents and…

Machine Learning · Computer Science 2018-12-03 Tiehang Duan , Qi Lou , Sargur N. Srihari , Xiaohui Xie

Enumeration problems related to words avoiding patterns as well as permutations that contain the pattern $123$ exactly once have been studied in great detail. However, the problem of enumerating words that contain the pattern $123$ exactly…

Combinatorics · Mathematics 2017-12-27 Mingjia Yang

Recently, Kitaev [Ki2] introduced partially ordered generalized patterns (POGPs) in the symmetric group, which further generalize the generalized permutation patterns introduced by Babson and Steingr\'imsson [BS]. A POGP p is a GP some of…

Combinatorics · Mathematics 2007-05-23 S. Kitaev , T. Mansour

In this paper, we first reviewed several biclustering methods that are used to identify the most significant clusters in gene expression data. Here we mainly focused on the SSVD(sparse SVD) method and tried a new sparse penalty named…

Machine Learning · Statistics 2023-09-01 Jiqiang Wang

We present three simple algorithms to uniformly generate `Fibonacci words' (i.e., some words that are enumerated by Fibonacci numbers), Schr{\"o}der trees of size $n$ and Motzkin left factors of size $n$ and final height $h$. These…

Discrete Mathematics · Computer Science 2023-03-17 Laurent Alonso
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