200 citations · 731 across the 17 of their papers we have counts for
8 papers · 1 filter
Discovering Latent Groups for Robust Classification
Ankur Garg, Ulrich Aïvodji, Samira Ebrahimi Kahou +1
Machine learning models exploit spurious correlations, achieving high average accuracy but failing disproportionately on underrepresented subgroups. Existing methods address this b…
Empowering Clinicians with Medical Decision Transformers: A Framework for Sepsis Treatment
Aamer Abdul Rahman, Pranav Agarwal, Rita Noumeir +3
Offline reinforcement learning has shown promise for solving tasks in safety-critical settings, such as clinical decision support. Its application, however, has been limited by the…
Learning Robust Dynamics through Variational Sparse Gating
Arnav Kumar Jain, Shivakanth Sujit, Shruti Joshi +3
Learning world models from their sensory inputs enables agents to plan for actions by imagining their future outcomes. World models have previously been shown to improve sample-eff…
Accounting for Variance in Machine Learning Benchmarks
Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi +14
Strong empirical evidence that one machine-learning algorithm A outperforms another one B ideally calls for multiple trials optimizing the learning pipeline over sources of variati…
Towards Deep Conversational Recommendations
Raymond Li, Samira Kahou, Hannes Schulz +3
There has been growing interest in using neural networks and deep learning techniques to create dialogue systems. Conversational recommendation is an interesting setting for the sc…
RATM: Recurrent Attentive Tracking Model
Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic
We present an attention-based modular neural framework for computer vision. The framework uses a soft attention mechanism allowing models to be trained with gradient descent. It co…
EmoNets: Multimodal deep learning approaches for emotion recognition in video
Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin +15
The task of the emotion recognition in the wild (EmotiW) Challenge is to assign one of seven emotions to short video clips extracted from Hollywood style movies. The videos depict…
Modeling sequential data using higher-order relational features and predictive training
Vincent Michalski, Roland Memisevic, Kishore Konda
Bi-linear feature learning models, like the gated autoencoder, were proposed as a way to model relationships between frames in a video. By minimizing reconstruction error of one fr…