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10/23/2022
The Curious Case of Absolute Position Embeddings
Transformer language models encode the notion of word order using positi...
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06/21/2022
Questions Are All You Need to Train a Dense Passage Retriever
We introduce ART, a new corpus-level autoencoding approach for training ...
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04/15/2022
Improving Passage Retrieval with Zero-Shot Question Generation
We propose a simple and effective re-ranking method for improving passag...
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03/08/2022
New Insights on Reducing Abrupt Representation Change in Online Continual Learning
In the online continual learning paradigm, agents must learn from a chan...
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02/28/2022
Estimating causal effects with optimization-based methods: A review and empirical comparison
In the absence of randomized controlled and natural experiments, it is n...
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02/20/2022
Efficient Continual Learning Ensembles in Neural Network Subspaces
A growing body of research in continual learning focuses on the catastro...
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02/14/2022
Robust Policy Learning over Multiple Uncertainty Sets
Reinforcement learning (RL) agents need to be robust to variations in sa...
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01/05/2022
A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions
Estimating value functions is a core component of reinforcement learning...
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10/13/2021
Block Contextual MDPs for Continual Learning
In reinforcement learning (RL), when defining a Markov Decision Process ...
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06/21/2021
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
We consider the offline reinforcement learning (RL) setting where the ag...
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06/20/2021
Do Encoder Representations of Generative Dialogue Models Encode Sufficient Information about the Task ?
Predicting the next utterance in dialogue is contingent on encoding of u...
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06/20/2021
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss
Neural models trained for next utterance generation in dialogue task lea...
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06/16/2021
SPeCiaL: Self-Supervised Pretraining for Continual Learning
This paper presents SPeCiaL: a method for unsupervised pretraining of re...
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06/07/2021
Correcting Momentum in Temporal Difference Learning
A common optimization tool used in deep reinforcement learning is moment...
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05/31/2021
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs
We study the problem of Safe Policy Improvement (SPI) under constraints ...
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04/15/2021
Sometimes We Want Translationese
Rapid progress in Neural Machine Translation (NMT) systems over the last...
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04/14/2021
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little
A possible explanation for the impressive performance of masked language...
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04/11/2021
Reducing Representation Drift in Online Continual Learning
We study the online continual learning paradigm, where agents must learn...
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03/14/2021
Quasi-Equivalence Discovery for Zero-Shot Emergent Communication
Effective communication is an important skill for enabling information e...
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02/19/2021
Model-Invariant State Abstractions for Model-Based Reinforcement Learning
Accuracy and generalization of dynamics models is key to the success of ...
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02/14/2021
Domain Adversarial Reinforcement Learning
We consider the problem of generalization in reinforcement learning wher...
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02/11/2021
Multi-Task Reinforcement Learning with Context-based Representations
The benefit of multi-task learning over single-task learning relies on t...
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02/05/2021
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs
Real-world knowledge graphs are often characterized by low-frequency rel...
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01/13/2021
COVID-19 Deterioration Prediction via Self-Supervised Representation Learning and Multi-Image Prediction
The rapid spread of COVID-19 cases in recent months has strained hospita...
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12/30/2020
Unnatural Language Inference
Natural Language Understanding has witnessed a watershed moment with the...
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12/03/2020
Intervention Design for Effective Sim2Real Transfer
The goal of this work is to address the recent success of domain randomi...
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10/29/2020
Exploring Zero-Shot Emergent Communication in Embodied Multi-Agent Populations
Effective communication is an important skill for enabling information e...
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10/07/2020
Regularized Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) aims to facilitate a learner's abil...
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09/28/2020
Novelty Search in representational space for sample efficient exploration
We present a new approach for efficient exploration which leverages a lo...
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08/26/2020
Constrained Markov Decision Processes via Backward Value Functions
Although Reinforcement Learning (RL) algorithms have found tremendous su...
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08/24/2020
How To Evaluate Your Dialogue System: Probe Tasks as an Alternative for Token-level Evaluation Metrics
Though generative dialogue modeling is widely seen as a language modelin...
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07/14/2020
Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP
Multi-task reinforcement learning is a rich paradigm where information f...
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07/06/2020
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?
We investigate whether Jacobi preconditioning, accounting for the bootst...
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07/03/2020
Deep interpretability for GWAS
Genome-Wide Association Studies are typically conducted using linear mod...
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06/23/2020
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization
Adversarial imitation learning alternates between learning a discriminat...
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05/07/2020
Plan2Vec: Unsupervised Representation Learning by Latent Plans
In this paper we introduce plan2vec, an unsupervised representation lear...
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05/06/2020
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM
We present Korbit, a large-scale, open-domain, mixed-interface, dialogue...
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05/05/2020
Automated Personalized Feedback Improves Learning Gains in an Intelligent Tutoring System
We investigate how automated, data-driven, personalized feedback in a la...
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05/01/2020
Learning an Unreferenced Metric for Online Dialogue Evaluation
Evaluating the quality of a dialogue interaction between two agents is a...
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03/27/2020
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)
One of the challenges in machine learning research is to ensure that pre...
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03/14/2020
Evaluating Logical Generalization in Graph Neural Networks
Recent research has highlighted the role of relational inductive biases ...
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03/13/2020
Interference and Generalization in Temporal Difference Learning
We study the link between generalization and interference in temporal-di...
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03/12/2020
Invariant Causal Prediction for Block MDPs
Generalization across environments is critical to the successful applica...
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03/09/2020
Stable Policy Optimization via Off-Policy Divergence Regularization
Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization...
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02/28/2020
The importance of transparency and reproducibility in artificial intelligence research
In their study, McKinney et al. showed the high potential of artificial ...
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02/24/2020
Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic
Multi-agent adversarial inverse reinforcement learning (MA-AIRL) is a re...
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02/07/2020
Provably efficient reconstruction of policy networks
Recent research has shown that learning poli-cies parametrized by large ...
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01/31/2020
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning
Accurate reporting of energy and carbon usage is essential for understan...
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11/20/2019
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking
The ability to detect and track objects in the visual world is a crucial...
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11/19/2019
