Publications related to Self-supervised Pre-training Enhances Change Detection in Sentinel-2 Imagery

Extracting and Locating Temporal Motifs in Video Scenes Using a Hierarchical Non Parametric Bayesian Model

Jean-Marc Odobez, Rémi Emonet, Jagannadan Varadarajan

In this paper, we present an unsupervised method for mining activities in videos. From unlabeled video sequences of a scene, our method can automatically recover what are the recurrent temporal activity patterns (or motifs) and when they occur. Using non p ...

2011

Multiple task learning in recurrent neural networks using layered reservoirs

Martin Hasler, Ali Ajdari Rad, Mahdi Jalili

In this paper, to learn multiple tasks sharing same inputs, a two-layer architecture for a reservoir based recurrent neural network is proposed. The inputs are fed into the general workspace layer where the weights are adapted to provide maximum informatio ...

2009

Learning and Predicting Multimodal Daily Life Patterns from Cell Phones

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In this paper, we investigate the multimodal nature of cell phone data in terms of discovering recurrent and rich patterns in people's lives. We present a method that can discover routines from multiple modalities (location and proximity) jointly modeled, ...

2009

Machine learning approaches to text representation using unlabeled data

Mikaela Keller

With the rapid expansion in the use of computers for producing digitalized textual documents, the need of automatic systems for organizing and retrieving the information contained in large databases has become essential. In general, information retrieval s ...

EPFL2008

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David Grangier

In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...

EPFL2008

Machine Learning for Information Retrieval

David Grangier

In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...

École Polytechnique Fédérale de Lausanne2008

Machine Learning for Information Retrieval

David Grangier

In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. Thisidentifica ...

IDIAP2008

Machine Learning Approaches to Text Representation using Unlabeled Data

Mikaela Keller

With the rapid expansion in the use of computers for producing digitalized textual documents, the need of automatic systems for organizing and retrieving the information contained in large databases has become essential. In general, information retrieval s ...

Ecole Polytechnique Fédérale de Lausanne2006

Machine Learning Approaches to Text Representation using Unlabeled Data

Mikaela Keller

With the rapid expansion in the use of computers for producing digitalized textual documents, the need of automatic systems for organizing and retrieving the information contained in large databases has become essential. In general, information retrieval s ...

IDIAP2006

Semi-supervised Adapted HMMs for Unusual Event Detection

Daniel Gatica-Perez, Samy Bengio, Dong Zhang

We address the problem of temporal unusual event detection. Unusual events are characterized by a number of features (rarity, unexpectedness, and relevance) that limit the application of traditional supervised model-based approaches. We propose a semi-supe ...

2005

Self-supervised Pre-training Enhances Change Detection in Sentinel-2 Imagery

Graph Chatbot

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Extracting and Locating Temporal Motifs in Video Scenes Using a Hierarchical Non Parametric Bayesian Model

Multiple task learning in recurrent neural networks using layered reservoirs

Learning and Predicting Multimodal Daily Life Patterns from Cell Phones

Machine learning approaches to text representation using unlabeled data

Machine learning for information retrieval

Machine Learning for Information Retrieval

Machine Learning for Information Retrieval

Machine Learning Approaches to Text Representation using Unlabeled Data

Machine Learning Approaches to Text Representation using Unlabeled Data

Semi-supervised Adapted HMMs for Unusual Event Detection

Multiple task learning in recurrent neural networks using layered reservoirs

Learning and Predicting Multimodal Daily Life Patterns from Cell Phones

Machine learning approaches to text representation using unlabeled data

Machine learning for information retrieval

Extracting and Locating Temporal Motifs in Video Scenes Using a Hierarchical Non Parametric Bayesian Model

Machine Learning for Information Retrieval

Machine Learning for Information Retrieval

Machine Learning Approaches to Text Representation using Unlabeled Data

Machine Learning Approaches to Text Representation using Unlabeled Data

Semi-supervised Adapted HMMs for Unusual Event Detection