Publications associées à Intuitive statistics

Multi-Dimensional Explanation of Target Variables from Documents

Boi Faltings, Claudiu-Cristian Musat, Diego Matteo Antognini

Automated predictions require explanations to be interpretable by humans. Past work used attention and rationale mechanisms to find words that predict the target variable of a document. Often though, they result in a tradeoff between noisy explanations or ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

Protecting Mobile Food Diaries from Getting too Personal

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Smartphone applications that use passive sensing to support human health and well-being primarily rely on: (a) generating low-dimensional representations from high-dimensional data streams; (b) making inferences regarding user behavior; and (c) using those ...

Association for Computing Machinery2020

A Bayesian Model of Individual Differences and Flexibility in Inductive Reasoning for Categorization of Examples

Pierre Dillenbourg, Jennifer Kaitlyn Olsen, Louis Pierre Faucon

Inductive reasoning is an important educational practice but can be difficult for teachers to support in the classroom due to the high level of preparation and classroom time needed to choose the teaching materials that challenge students' current views. I ...

ASSOC COMPUTING MACHINERY2020

Efficient inference for genetic association studies with multiple outcomes

Anthony Christopher Davison, Jörg Hager, Hélène Ruffieux

Combined inference for heterogeneous high-dimensional data is critical in modern biology, where clinical and various kinds of molecular data may be available from a single study. Classical genetic association studies regress a single clinical outcome on ma ...

Oxford University Press2017

Learning Search Strategies from Human Demonstrations

Guillaume Pierre Luc De Chambrier

Decision making and planning with partial state information is a problem faced by all forms of intelligent entities. The formulation of a problem under partial state information leads to an exorbitant set of choices with associated probabilistic outcomes m ...

EPFL2016

Kullback-Leibler Proximal Variational Inference

Pascal Fua, François Fleuret, Pierre Bruno Baqué, Mohammad Emtiyaz Khan

We propose a new variational inference method based on a proximal framework that uses the Kullback-Leibler (KL) divergence as the proximal term. We make two contributions towards exploiting the geometry and structure of the variational bound. Firstly, we p ...

2015

Limits on Support Recovery with Probabilistic Models: An Information-Theoretic Framework

Volkan Cevher, Jonathan Mark Scarlett

The support recovery problem consists of deter- mining a sparse subset of a set of variables that is relevant in generating a set of observations, and arises in a diverse range of settings such as group testing, compressive sensing, and subset selection in ...

2015

Inferences of Demography and Selection in an African Population of Drosophila melanogaster

Jeffrey David Jensen

It remains a central problem in population genetics to infer the past action of natural selection, and these inferences pose a challenge because demographic events will also substantially affect patterns of polymorphism and divergence. Thus it is imperativ ...

Genetics Society of America2013

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Intuitive statistics

Learning Analytics for Adaptive and Self-Improving Learning Environments for Inductive Teaching

Multi-Dimensional Explanation of Target Variables from Documents

Protecting Mobile Food Diaries from Getting too Personal

The Learnability of the Grammar of Jazz: Bayesian Inference of Hierarchical Structures in Harmony

A Bayesian Model of Individual Differences and Flexibility in Inductive Reasoning for Categorization of Examples

Efficient inference for genetic association studies with multiple outcomes

Learning Search Strategies from Human Demonstrations

Kullback-Leibler Proximal Variational Inference

Limits on Support Recovery with Probabilistic Models: An Information-Theoretic Framework

Inferences of Demography and Selection in an African Population of Drosophila melanogaster

Graph Chatbot

Chattez avec Graph Search

A Bayesian Model of Individual Differences and Flexibility in Inductive Reasoning for Categorization of Examples

Protecting Mobile Food Diaries from Getting too Personal

Multi-Dimensional Explanation of Target Variables from Documents

Learning Analytics for Adaptive and Self-Improving Learning Environments for Inductive Teaching

Inferences of Demography and Selection in an African Population of Drosophila melanogaster

The Learnability of the Grammar of Jazz: Bayesian Inference of Hierarchical Structures in Harmony

Efficient inference for genetic association studies with multiple outcomes

Learning Search Strategies from Human Demonstrations

Kullback-Leibler Proximal Variational Inference

Limits on Support Recovery with Probabilistic Models: An Information-Theoretic Framework