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08/24/2023
Code Llama: Open Foundation Models for Code
We release Code Llama, a family of large language models for code based ...
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05/19/2023
Group fairness without demographics using social networks
Group fairness is a popular approach to prevent unfavorable treatment of...
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02/16/2023
Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifiers
Disaggregated performance metrics across demographic groups are a hallma...
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10/26/2022
Leveraging Demonstrations with Latent Space Priors
Demonstrations provide insight into relevant state or action space regio...
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10/18/2022
Contextual bandits with concave rewards, and an application to fair ranking
We consider Contextual Bandits with Concave Rewards (CBCR), a multi-obje...
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10/05/2022
Parity in Markets – Methods, Costs, and Consequences
Fisher markets are those where buyers with budgets compete for scarce it...
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09/13/2022
Fast online ranking with fairness of exposure
As recommender systems become increasingly central for sorting and prior...
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07/20/2022
Measuring and signing fairness as performance under multiple stakeholder distributions
As learning machines increase their influence on decisions concerning hu...
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04/02/2022
Optimizing generalized Gini indices for fairness in rankings
There is growing interest in designing recommender systems that aim at b...
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02/15/2022
Fairness Indicators for Systematic Assessments of Visual Feature Extractors
Does everyone equally benefit from computer vision systems? Answers to t...
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10/28/2021
Two-sided fairness in rankings via Lorenz dominance
We consider the problem of generating rankings that are fair towards bot...
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10/20/2021
Hierarchical Skills for Efficient Exploration
In reinforcement learning, pre-trained low-level skills have the potenti...
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05/19/2021
Online Selection of Diverse Committees
Citizens' assemblies need to represent subpopulations according to their...
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04/29/2021
Online certification of preference-based fairness for personalized recommender systems
We propose to assess the fairness of personalized recommender systems in...
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04/20/2021
Gradient Matching for Domain Generalization
Machine learning systems typically assume that the distributions of trai...
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04/17/2021
A Self-Supervised Auxiliary Loss for Deep RL in Partially Observable Settings
In this work we explore an auxiliary loss useful for reinforcement learn...
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05/26/2020
End-to-End Object Detection with Transformers
We present a new method that views object detection as a direct set pred...
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05/06/2020
Learning Adaptive Exploration Strategies in Dynamic Environments Through Informed Policy Regularization
We study the problem of learning exploration-exploitation strategies tha...
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04/10/2020
Tensor Decompositions for temporal knowledge base completion
Most algorithms for representation learning and link prediction in relat...
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03/05/2020
On the Convergence of Adam and Adagrad
We provide a simple proof of the convergence of the optimization algorit...
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11/27/2019
Music Source Separation in the Waveform Domain
Source separation for music is the task of isolating contributions, or s...
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10/19/2019
A Structured Prediction Approach for Generalization in Cooperative Multi-Agent Reinforcement Learning
Effective coordination is crucial to solve multi-agent collaborative (MA...
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09/03/2019
Demucs: Deep Extractor for Music Sources with extra unlabeled data remixed
We study the problem of source separation for music using deep learning ...
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06/28/2019
Growing Action Spaces
In complex tasks, such as those with large combinatorial action spaces, ...
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12/17/2018
Fully Convolutional Speech Recognition
Current state-of-the-art speech recognition systems build on recurrent n...
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12/09/2018
To Reverse the Gradient or Not: An Empirical Comparison of Adversarial and Multi-task Learning in Speech Recognition
Transcribed datasets typically contain speaker identity for each instanc...
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11/30/2018
Forward Modeling for Partial Observation Strategy Games - A StarCraft Defogger
We formulate the problem of defogging as state estimation and future sta...
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11/21/2018
High-Level Strategy Selection under Partial Observability in StarCraft: Brood War
We consider the problem of high-level strategy selection in the adversar...
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10/23/2018
SING: Symbol-to-Instrument Neural Generator
Recent progress in deep learning for audio synthesis opens the way to mo...
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06/19/2018
Canonical Tensor Decomposition for Knowledge Base Completion
The problem of Knowledge Base Completion can be framed as a 3rd-order bi...
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06/19/2018
End-to-End Speech Recognition From the Raw Waveform
State-of-the-art speech recognition systems rely on fixed, hand-crafted ...
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05/28/2018
Value Propagation Networks
We present Value Propagation (VProp), a parameter-efficient differentiab...
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11/03/2017
Learning Filterbanks from Raw Speech for Phone Recognition
We train a bank of complex filters that operates on the raw waveform and...
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06/01/2017
Fader Networks: Manipulating Images by Sliding Attributes
This paper introduces a new encoder-decoder architecture that is trained...
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04/28/2017
Parseval Networks: Improving Robustness to Adversarial Examples
We introduce Parseval networks, a form of deep neural networks in which ...
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12/13/2016
Improving Neural Language Models with a Continuous Cache
We propose an extension to neural network language models to adapt their...
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11/01/2016
TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games
We present TorchCraft, a library that enables deep learning research on ...
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09/21/2016
How should we evaluate supervised hashing?
Hashing produces compact representations for documents, to perform tasks...
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09/10/2016
Episodic Exploration for Deep Deterministic Policies: An Application to StarCraft Micromanagement Tasks
We consider scenarios from the real-time strategy game StarCraft as new ...
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06/02/2015
Combining Two And Three-Way Embeddings Models for Link Prediction in Knowledge Bases
This paper tackles the problem of endogenous link prediction for Knowled...
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12/08/2012