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Structured and grounded representation of text is typically formalized by closed information extraction, the problem of extracting an exhaustive set of (subject, relation, object) triplets that are consistent with a predefined set of…

Computation and Language · Computer Science 2022-04-14 Martin Josifoski , Nicola De Cao , Maxime Peyrard , Fabio Petroni , Robert West

We study goodness-of-fit of discrete distributions in the distributed setting, where samples are divided between multiple users who can only release a limited amount of information about their samples due to various information constraints.…

Data Structures and Algorithms · Computer Science 2019-07-23 Jayadev Acharya , Clément L. Canonne , Yanjun Han , Ziteng Sun , Himanshu Tyagi

Inquiries such as whether a task A depends on a task B, whether an author A has been influenced by a paper B, whether a certain protein is associated with a specific biological process or molecular function, or whether class A inherits from…

Data Structures and Algorithms · Computer Science 2024-05-02 Giorgos Kritikakis , Ioannis G Tollis

Consistent query answering over a database that violates primary key constraints is a classical hard problem in database research that has been traditionally dealt with logic programming. However, the applicability of existing logic-based…

Artificial Intelligence · Computer Science 2015-07-23 Marco Manna , Francesco Ricca , Giorgio Terracina

Graph compression is a data analysis technique that consists in the replacement of parts of a graph by more general structural patterns in order to reduce its description length. It notably provides interesting exploration tools for the…

Data Structures and Algorithms · Computer Science 2018-07-19 Robin Lamarche-Perrin

This paper extends the sample complexity theory for ill-posed inverse problems developed in a recent work by the authors [`Compressed sensing for inverse problems and the sample complexity of the sparse Radon transform', J. Eur. Math. Soc.,…

Functional Analysis · Mathematics 2025-01-06 Giovanni S. Alberti , Alessandro Felisi , Matteo Santacesaria , S. Ivan Trapasso

In typical high dimensional statistical inference problems, confidence intervals and hypothesis tests are performed for a low dimensional subset of model parameters under the assumption that the parameters of interest are unconstrained.…

Methodology · Statistics 2019-11-19 Ming Yu , Varun Gupta , Mladen Kolar

Neural conversation models tend to generate safe, generic responses for most inputs. This is due to the limitations of likelihood-based decoding objectives in generation tasks with diverse outputs, such as conversation. To address this…

Computation and Language · Computer Science 2018-09-06 Ashutosh Baheti , Alan Ritter , Jiwei Li , Bill Dolan

Constraint problems can be trivially solved in parallel by exploring different branches of the search tree concurrently. Previous approaches have focused on implementing this functionality in the solver, more or less transparently to the…

Artificial Intelligence · Computer Science 2010-08-26 Lars Kotthoff , Neil C. A. Moore

Consider the case where a programmer has written some part of a program, but has left part of the program (such as a method or a function body) incomplete. The goal is to use the context surrounding the missing code to automatically 'figure…

Software Engineering · Computer Science 2020-07-28 Rohan Mukherjee , Swarat Chaudhuri , Chris Jermaine

While going deeper has been witnessed to improve the performance of convolutional neural networks (CNN), going smaller for CNN has received increasing attention recently due to its attractiveness for mobile/embedded applications. It remains…

Computer Vision and Pattern Recognition · Computer Science 2017-06-14 Zhe Li , Xiaoyu Wang , Xutao Lv , Tianbao Yang

We address the problem of learning a distributed representation of entities in a relational database using a low-dimensional embedding. Low-dimensional embeddings aim to encapsulate a concise vector representation for an underlying dataset…

Databases · Computer Science 2020-05-14 Siddhant Arora , Srikanta Bedathur

A learning task, understood as the problem of fitting a parametric model from supervised data, fundamentally requires the dataset to be large enough to be representative of the underlying distribution of the source. When data is limited,…

Machine Learning · Computer Science 2025-11-18 Leopoldo Agorio , Juan Cerviño , Miguel Calvo-Fullana , Alejandro Ribeiro , Juan Andrés Bazerque

When knowledge is obtained from a database, it is only possible to deduce confidence intervals for probability values. With confidence intervals replacing point values, the results in the set covering model include interval constraints for…

Artificial Intelligence · Computer Science 2013-04-10 Richard E. Neapolitan , James Kenevan

Conventional deep learning prioritizes unconstrained optimization, yet biological systems operate under strict metabolic constraints. We propose that these physical constraints shape dynamics to function not as limitations, but as a…

Machine Learning · Computer Science 2026-01-23 Xia Chen

Exploring the generalization of a text-to-SQL parser is essential for a system to automatically adapt the real-world databases. Previous works provided investigations focusing on lexical diversity, including the influence of the synonym and…

Artificial Intelligence · Computer Science 2023-01-24 Jieyu Li , Lu Chen , Ruisheng Cao , Su Zhu , Hongshen Xu , Zhi Chen , Hanchong Zhang , Kai Yu

Integrity constraints in databases have been studied extensively since the 1980s, and they are considered essential to guarantee database integrity. In recent years, several authors have studied how the same notion can be adapted to…

Databases · Computer Science 2017-08-09 Luís Cruz-Filipe , Isabel Nunes , Peter Schneider-Kamp

Among daily tasks of database administrators (DBAs), the analysis of query workloads to identify schema issues and improving performances is crucial. Although DBAs can easily pinpoint queries repeatedly causing performance issues, it…

Artificial Intelligence · Computer Science 2021-08-10 Youcef Remil , Anes Bendimerad , Romain Mathonat , Philippe Chaleat , Mehdi Kaytoue

Current mathematical frameworks for predicting the flux state and macromolecular composition of the cell do not rely on thermodynamic constraints to determine the spontaneous direction of reactions. These predictions may be biologically…

Optimization and Control · Mathematics 2020-08-14 Amir Akbari , Bernhard O. Palsson

Past research on probabilistic databases has studied the problem of answering queries on a static database. Application scenarios of probabilistic databases however often involve the conditioning of a database using additional information…

Databases · Computer Science 2008-06-16 Christoph Koch , Dan Olteanu
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