Sarath Chandar

research

∙ 08/20/2023

Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabi

Cooperative Multi-agent Reinforcement Learning (MARL) algorithms with Ze...

0 Hadi Nekoei, et al. ∙

research

∙ 07/31/2023

Lookbehind Optimizer: k steps back, 1 step forward

The Lookahead optimizer improves the training stability of deep neural n...

0 Gonçalo Mordido, et al. ∙

research

∙ 07/18/2023

Promoting Exploration in Memory-Augmented Adam using Critical Momenta

Adaptive gradient-based optimizers, particularly Adam, have left their m...

0 Pranshu Malviya, et al. ∙

research

∙ 06/30/2023

Thompson sampling for improved exploration in GFlowNets

Generative flow networks (GFlowNets) are amortized variational inference...

0 Jarrid Rector-Brooks, et al. ∙

research

∙ 05/24/2023

Measuring the Knowledge Acquisition-Utilization Gap in Pretrained Language Models

While pre-trained language models (PLMs) have shown evidence of acquirin...

0 Amirhossein Kazemnejad, et al. ∙

research

∙ 05/22/2023

Should We Attend More or Less? Modulating Attention for Fairness

The abundance of annotated data in natural language processing (NLP) pos...

0 Abdelrahman Zayed, et al. ∙

research

∙ 05/16/2023

Towards Lifelong Learning for Software Analytics Models: Empirical Study on Brown Build and Risk Prediction

Nowadays, software analytics tools using machine learning (ML) models to...

0 Doriane Olewicki, et al. ∙

research

∙ 03/16/2023

Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning

Efficient exploration is critical in cooperative deep Multi-Agent Reinfo...

0 Xutong Zhao, et al. ∙

research

∙ 03/15/2023

Replay Buffer With Local Forgetting for Adaptive Deep Model-Based Reinforcement Learning

One of the key behavioral characteristics used in neuroscience to determ...

0 Ali Rahimi-Kalahroudi, et al. ∙

research

∙ 02/06/2023

Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning

Decentralized cooperative multi-agent deep reinforcement learning (MARL)...

0 Hadi Nekoei, et al. ∙

research

∙ 11/20/2022

Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness

Data-driven predictive solutions predominant in commercial applications ...

0 Abdelrahman Zayed, et al. ∙

research

∙ 11/18/2022

Sharpness-Aware Training for Accurate Inference on Noisy DNN Accelerators

Energy-efficient deep neural network (DNN) accelerators are prone to non...

0 Gonçalo Mordido, et al. ∙

research

∙ 11/09/2022

Local Structure Matters Most in Most Languages

Many recent perturbation studies have found unintuitive results on what ...

0 Louis Clouâtre, et al. ∙

research

∙ 11/09/2022

Detecting Languages Unintelligible to Multilingual Models through Local Structure Probes

Providing better language tools for low-resource and endangered language...

0 Louis Clouâtre, et al. ∙

research

∙ 10/27/2022

Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?

Segmentation of Multiple Sclerosis (MS) lesions is a challenging problem...

0 Enamundram Naga Karthik, et al. ∙

research

∙ 08/03/2022

Improving Meta-Learning Generalization with Activation-Based Early-Stopping

Meta-Learning algorithms for few-shot learning aim to train neural netwo...

4 Simon Guiroy, et al. ∙

research

∙ 07/10/2022

An Introduction to Lifelong Supervised Learning

This primer is an attempt to provide a detailed summary of the different...

21 Shagun Sodhani, et al. ∙

research

∙ 04/25/2022

Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods

In recent years, a growing number of deep model-based reinforcement lear...

12 Yi Wan, et al. ∙

research

∙ 02/01/2022

Improving Sample Efficiency of Value Based Models Using Attention and Vision Transformers

Much of recent Deep Reinforcement Learning success is owed to the neural...

0 Amir Ardalan Kalantari, et al. ∙

research

∙ 12/16/2021

An Empirical Investigation of the Role of Pre-training in Lifelong Learning

The lifelong learning paradigm in machine learning is an attractive alte...

5 Sanket Vaibhav Mehta, et al. ∙

research

∙ 10/13/2021

Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers

Empirical science of neural scaling laws is a rapidly growing area of si...

10 Gabriele Prato, et al. ∙

research

∙ 08/10/2021

Post-hoc Interpretability for Neural NLP: A Survey

Natural Language Processing (NLP) models have become increasingly more c...

23 Andreas Madsen, et al. ∙

research

∙ 07/29/2021

Demystifying Neural Language Models' Insensitivity to Word-Order

Recent research analyzing the sensitivity of natural language understand...

0 Louis Clouâtre, et al. ∙

research

∙ 06/20/2021

Memory Augmented Optimizers for Deep Learning

Popular approaches for minimizing loss in data-driven learning often inv...

0 Paul-Aymeric McRae, et al. ∙

research

∙ 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...

11 Prasanna Parthasarathi, et al. ∙

research

∙ 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...

6 Prasanna Parthasarathi, et al. ∙

research

∙ 05/11/2021

TAG: Task-based Accumulated Gradients for Lifelong learning

When an agent encounters a continual stream of new tasks in the lifelong...

0 Pranshu Malviya, et al. ∙

research

∙ 03/04/2021

Continuous Coordination As a Realistic Scenario for Lifelong Learning

Current deep reinforcement learning (RL) algorithms are still highly tas...

0 Hadi Nekoei, et al. ∙

research

∙ 12/23/2020

IIRC: Incremental Implicitly-Refined Classification

We introduce the "Incremental Implicitly-Refined Classi-fication (IIRC)"...

7 Mohamed Abdelsalam, et al. ∙

research

∙ 10/08/2020

Maximum Reward Formulation In Reinforcement Learning

Reinforcement learning (RL) algorithms typically deal with maximizing th...

23 Sai Krishna Gottipati, et al. ∙

research

∙ 09/15/2020

MLMLM: Link Prediction with Mean Likelihood Masked Language Model

Knowledge Bases (KBs) are easy to query, verifiable, and interpretable. ...

5 Louis Clouâtre, et al. ∙

research

∙ 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...

11 Prasanna Parthasarathi, et al. ∙

research

∙ 07/18/2020

Slot Contrastive Networks: A Contrastive Approach for Representing Objects

Unsupervised extraction of objects from low-level visual data is an impo...

6 Evan Racah, et al. ∙

research

∙ 07/07/2020

The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning

Deep model-based Reinforcement Learning (RL) has the potential to substa...

2 Harm van Seijen, et al. ∙

research

∙ 06/14/2020

PatchUp: A Regularization Technique for Convolutional Neural Networks

Large capacity deep learning models are often prone to a high generaliza...

42 Mojtaba Faramarzi, et al. ∙

research

∙ 04/26/2020

Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning

Over the last decade, there has been significant progress in the field o...

4 Sai Krishna Gottipati, et al. ∙

research

∙ 06/04/2019

Towards Lossless Encoding of Sentences

A lot of work has been done in the field of image compression via machin...

0 Gabriele Prato, et al. ∙

research

∙ 06/04/2019

Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study

Neural generative models have been become increasingly popular when buil...

2 Chinnadhurai Sankar, et al. ∙

research

∙ 05/27/2019

Structure Learning for Neural Module Networks

Neural Module Networks, originally proposed for the task of visual quest...

1 Vardaan Pahuja, et al. ∙

research

∙ 02/11/2019

Edge Replacement Grammars: A Formal Language Approach for Generating Graphs

Graphs are increasingly becoming ubiquitous as models for structured dat...

0 Revanth Reddy, et al. ∙

research

∙ 02/01/2019

The Hanabi Challenge: A New Frontier for AI Research

From the early days of computing, games have been important testbeds for...

54 Nolan Bard, 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

∙ 11/26/2018

Environments for Lifelong Reinforcement Learning

To achieve general artificial intelligence, reinforcement learning (RL) ...

0 Khimya Khetarpal, et al. ∙

research

∙ 11/16/2018

On Training Recurrent Neural Networks for Lifelong Learning

Capacity saturation and catastrophic forgetting are the central challeng...

0 Shagun Sodhani, et al. ∙

research

∙ 05/17/2018

Language Expansion In Text-Based Games

Text-based games are suitable test-beds for designing agents that can le...

0 Ghulam Ahmed Ansari, et al. ∙

research

∙ 01/31/2018

Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph

While conversing with chatbots, humans typically tend to ask many questi...

0 Amrita Saha, et al. ∙

research

∙ 01/20/2018

A Deep Reinforcement Learning Chatbot (Short Version)

We present MILABOT: a deep reinforcement learning chatbot developed by t...

0 Iulian V. Serban, et al. ∙

research

∙ 09/07/2017

A Deep Reinforcement Learning Chatbot

We present MILABOT: a deep reinforcement learning chatbot developed by t...

0 Iulian V. Serban, et al. ∙

research

∙ 01/30/2017

Memory Augmented Neural Networks with Wormhole Connections

Recent empirical results on long-term dependency tasks have shown that n...

0 Caglar Gulcehre, et al. ∙

research

∙ 11/23/2016

GuessWhat?! Visual object discovery through multi-modal dialogue

We introduce GuessWhat?!, a two-player guessing game as a testbed for re...

0 Harm de Vries, et al. ∙

Sarath Chandar

Featured Co-authors