Samira Ebrahimi Kahou

research

∙ 07/24/2023

Fairness Under Demographic Scarce Regime

Most existing works on fairness assume the model has full access to demo...

0 Patrik Joslin Kenfack, et al. ∙

research

∙ 07/12/2023

Transformers in Reinforcement Learning: A Survey

Transformers have significantly impacted domains like natural language p...

0 Pranav Agarwal, et al. ∙

research

∙ 06/19/2023

CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning

Before taking actions in an environment with more than one intelligent a...

0 Nikunj Gupta, et al. ∙

research

∙ 04/27/2023

Discovering Object-Centric Generalized Value Functions From Pixels

Deep Reinforcement Learning has shown significant progress in extracting...

1 Somjit Nath, et al. ∙

research

∙ 04/06/2023

Source-free Domain Adaptation Requires Penalized Diversity

While neural networks are capable of achieving human-like performance in...

0 Laya Rafiee Sevyeri, et al. ∙

research

∙ 12/15/2022

Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies

Reinforcement learning (RL) has shown great promise with algorithms lear...

0 Shivakanth Sujit, et al. ∙

research

∙ 11/28/2022

Pitfalls of Conditional Batch Normalization for Contextual Multi-Modal Learning

Humans have perfected the art of learning from multiple modalities throu...

0 Ivaxi Sheth, et al. ∙

research

∙ 11/15/2022

Automatic Evaluation of Excavator Operators using Learned Reward Functions

Training novice users to operate an excavator for learning different ski...

0 Pranav Agarwal, et al. ∙

research

∙ 11/10/2022

BERT on a Data Diet: Finding Important Examples by Gradient-Based Pruning

Current pre-trained language models rely on large datasets for achieving...

0 Mohsen Fayyaz, et al. ∙

research

∙ 10/24/2022

Learning Latent Structural Causal Models

Causal learning has long concerned itself with the accurate recovery of ...

0 Jithendaraa Subramanian, et al. ∙

research

∙ 09/20/2022

Locally Constrained Representations in Reinforcement Learning

The success of Reinforcement Learning (RL) heavily relies on the ability...

12 Somjit Nath, et al. ∙

research

∙ 08/22/2022

Prioritizing Samples in Reinforcement Learning with Reducible Loss

Most reinforcement learning algorithms take advantage of an experience r...

3 Shivakanth Sujit, et al. ∙

research

∙ 07/12/2022

Latent Variable Models for Bayesian Causal Discovery

Learning predictors that do not rely on spurious correlations involves b...

0 Jithendaraa Subramanian, et al. ∙

research

∙ 05/31/2022

FHIST: A Benchmark for Few-shot Classification of Histological Images

Few-shot learning has recently attracted wide interest in image classifi...

17 Fereshteh Shakeri, et al. ∙

research

∙ 09/07/2021

Simple Video Generation using Neural ODEs

Despite having been studied to a great extent, the task of conditional g...

0 David Kanaa, et al. ∙

research

∙ 03/01/2021

Accounting for Variance in Machine Learning Benchmarks

Strong empirical evidence that one machine-learning algorithm A outperfo...

23 Xavier Bouthillier, et al. ∙

research

∙ 02/19/2021

Latent Variable Nested Set Transformers AutoBots

Humans have the innate ability to attend to the most relevant actors in ...

0 Roger Girgis, et al. ∙

research

∙ 11/29/2020

Predicting Regional Locust Swarm Distribution with Recurrent Neural Networks

Locust infestation of some regions in the world, including Africa, Asia ...

0 Hadia Mohmmed Osman Ahmed Samil, et al. ∙

research

∙ 07/31/2019

An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation

Batch normalization has been widely used to improve optimization in deep...

1 Vincent Michalski, et al. ∙

research

∙ 01/22/2019

Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies

Modelling long-term dependencies is a challenge for recurrent neural net...

0 Sarath Chandar, et al. ∙

research

∙ 11/24/2018

Keep Drawing It: Iterative language-based image generation and editing

Conditional text-to-image generation approaches commonly focus on genera...

0 Alaaeldin El-Nouby, et al. ∙

research

∙ 02/22/2018

ChatPainter: Improving Text to Image Generation using Dialogue

Synthesizing realistic images from text descriptions on a dataset like M...

0 Shikhar Sharma, et al. ∙

research

∙ 10/19/2017

FigureQA: An Annotated Figure Dataset for Visual Reasoning

We introduce FigureQA, a visual reasoning corpus of over one million que...

0 Samira Ebrahimi Kahou, et al. ∙

research

∙ 06/13/2017

The "something something" video database for learning and evaluating visual common sense

Neural networks trained on datasets such as ImageNet have led to major a...

0 Raghav Goyal, et al. ∙

research

∙ 12/07/2016

ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events

Then detection and identification of extreme weather events in large-sca...

0 Evan Racah, et al. ∙

research

∙ 05/09/2016

Theano: A Python framework for fast computation of mathematical expressions

Theano is a Python library that allows to define, optimize, and evaluate...

0 The Theano Development Team, et al. ∙

research

∙ 03/17/2016

Do Deep Convolutional Nets Really Need to be Deep and Convolutional?

Yes, they do. This paper provides the first empirical demonstration that...

0 Gregor Urban, et al. ∙

research

∙ 03/05/2015

EmoNets: Multimodal deep learning approaches for emotion recognition in video

The task of the emotion recognition in the wild (EmotiW) Challenge is to...

0 Samira Ebrahimi Kahou, et al. ∙

research

∙ 12/19/2014

FitNets: Hints for Thin Deep Nets

While depth tends to improve network performances, it also makes gradien...

0 Adriana Romero, et al. ∙

Samira Ebrahimi Kahou

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