
Entropybased 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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SmoothI: Smooth Rank Indicators for Differentiable IR Metrics
Information retrieval (IR) systems traditionally aim to maximize metrics...
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Heavytailed Representations, Text Polarity Classification Data Augmentation
The dominant approaches to text representation in natural language rely ...
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Supervised Categorical Metric Learning with Schatten pNorms
Metric learning has been successful in learning new metrics adapted to n...
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Terminologybased 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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Char2char Generation with Reranking for the E2E NLG Challenge
This paper describes our submission to the E2E NLG Challenge. Recently, ...
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Dealing with Uncertain Inputs in Regression Trees
Treebased ensemble methods, as Random Forests and Gradient Boosted Tree...
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Deep kMeans: Jointly Clustering with kMeans and Learning Representations
We study in this paper the problem of jointly clustering and learning re...
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On Inductive Abilities of Latent Factor Models for Relational Learning
Latent factor models are increasingly popular for modeling multirelatio...
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Positionbased Content Attention for Time Series Forecasting with Sequencetosequence RNNs
We propose here an extended attention model for sequencetosequence rec...
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Knowledge Graph Completion via Complex Tensor Factorization
In statistical relational learning, knowledge graph completion deals wit...
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Complex Embeddings for Simple Link Prediction
In statistical relational learning, the link prediction problem is key t...
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LSHTC: A Benchmark for LargeScale Text Classification
LSHTC is a series of challenges which aims to assess the performance of ...
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Evaluation Measures for Hierarchical Classification: a unified view and novel approaches
Hierarchical classification addresses the problem of classifying items i...
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Eric Gaussier
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