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07/28/2023
Case Studies of Causal Discovery from IT Monitoring Time Series
Information technology (IT) systems are vital for modern businesses, han...
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06/14/2023
Hybrids of Constraint-based and Noise-based Algorithms for Causal Discovery from Time Series
Constraint-based and noise-based methods have been proposed to discover ...
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12/13/2022
Domain Adaptation for Dense Retrieval through Self-Supervision by Pseudo-Relevance Labeling
Although neural information retrieval has witnessed great improvements, ...
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05/19/2022
Inferring extended summary causal graphs from observational time series
This study addresses the problem of learning an extended summary causal ...
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04/13/2022
Where Do You Want To Invest? Predicting Startup Funding From Freely, Publicly Available Web Information
We consider in this paper the problem of predicting the ability of a sta...
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11/18/2021
The Power of Selecting Key Blocks with Local Pre-ranking for Long Document Information Retrieval
On a wide range of natural language processing and information retrieval...
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05/21/2021
Entropy-based Discovery of Summary Causal Graphs in Time Series
We address in this study the problem of learning a summary causal graph ...
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05/03/2021
SmoothI: Smooth Rank Indicators for Differentiable IR Metrics
Information retrieval (IR) systems traditionally aim to maximize metrics...
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03/25/2020
Heavy-tailed Representations, Text Polarity Classification Data Augmentation
The dominant approaches to text representation in natural language rely ...
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02/26/2020
Supervised Categorical Metric Learning with Schatten p-Norms
Metric learning has been successful in learning new metrics adapted to n...
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06/05/2019
Terminology-based Text Embedding for Computing Document Similarities on Technical Content
We propose in this paper a new, hybrid document embedding approach in or...
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11/04/2018
Char2char Generation with Reranking for the E2E NLG Challenge
This paper describes our submission to the E2E NLG Challenge. Recently, ...
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10/27/2018
Dealing with Uncertain Inputs in Regression Trees
Tree-based ensemble methods, as Random Forests and Gradient Boosted Tree...
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06/26/2018
Deep k-Means: Jointly Clustering with k-Means and Learning Representations
We study in this paper the problem of jointly clustering and learning re...
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09/17/2017
On Inductive Abilities of Latent Factor Models for Relational Learning
Latent factor models are increasingly popular for modeling multi-relatio...
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03/29/2017
Position-based Content Attention for Time Series Forecasting with Sequence-to-sequence RNNs
We propose here an extended attention model for sequence-to-sequence rec...
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02/22/2017
Knowledge Graph Completion via Complex Tensor Factorization
In statistical relational learning, knowledge graph completion deals wit...
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06/20/2016
Complex Embeddings for Simple Link Prediction
In statistical relational learning, the link prediction problem is key t...
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03/30/2015
LSHTC: A Benchmark for Large-Scale Text Classification
LSHTC is a series of challenges which aims to assess the performance of ...
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06/28/2013