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07/24/2023
Fairness Under Demographic Scarce Regime
Most existing works on fairness assume the model has full access to demo...
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07/12/2023
Transformers in Reinforcement Learning: A Survey
Transformers have significantly impacted domains like natural language p...
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06/19/2023
CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning
Before taking actions in an environment with more than one intelligent a...
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04/27/2023
Discovering Object-Centric Generalized Value Functions From Pixels
Deep Reinforcement Learning has shown significant progress in extracting...
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04/06/2023
Source-free Domain Adaptation Requires Penalized Diversity
While neural networks are capable of achieving human-like performance in...
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12/15/2022
Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies
Reinforcement learning (RL) has shown great promise with algorithms lear...
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11/28/2022
Pitfalls of Conditional Batch Normalization for Contextual Multi-Modal Learning
Humans have perfected the art of learning from multiple modalities throu...
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11/15/2022
Automatic Evaluation of Excavator Operators using Learned Reward Functions
Training novice users to operate an excavator for learning different ski...
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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...
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10/24/2022
Learning Latent Structural Causal Models
Causal learning has long concerned itself with the accurate recovery of ...
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09/20/2022
Locally Constrained Representations in Reinforcement Learning
The success of Reinforcement Learning (RL) heavily relies on the ability...
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08/22/2022
Prioritizing Samples in Reinforcement Learning with Reducible Loss
Most reinforcement learning algorithms take advantage of an experience r...
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07/12/2022
Latent Variable Models for Bayesian Causal Discovery
Learning predictors that do not rely on spurious correlations involves b...
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05/31/2022
FHIST: A Benchmark for Few-shot Classification of Histological Images
Few-shot learning has recently attracted wide interest in image classifi...
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09/07/2021
Simple Video Generation using Neural ODEs
Despite having been studied to a great extent, the task of conditional g...
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03/01/2021
Accounting for Variance in Machine Learning Benchmarks
Strong empirical evidence that one machine-learning algorithm A outperfo...
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02/19/2021
Latent Variable Nested Set Transformers AutoBots
Humans have the innate ability to attend to the most relevant actors in ...
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11/29/2020
Predicting Regional Locust Swarm Distribution with Recurrent Neural Networks
Locust infestation of some regions in the world, including Africa, Asia ...
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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...
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01/22/2019
Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies
Modelling long-term dependencies is a challenge for recurrent neural net...
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11/24/2018
Keep Drawing It: Iterative language-based image generation and editing
Conditional text-to-image generation approaches commonly focus on genera...
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02/22/2018
ChatPainter: Improving Text to Image Generation using Dialogue
Synthesizing realistic images from text descriptions on a dataset like M...
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10/19/2017
FigureQA: An Annotated Figure Dataset for Visual Reasoning
We introduce FigureQA, a visual reasoning corpus of over one million que...
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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...
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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...
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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...
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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...
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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...
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12/19/2014
