Sarath Chandar

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Ph.D. Student in Machine Learning at Université de Montré, Research Intern at IBM TJ Watson Research Lab

Demystifying Neural Language Models' Insensitivity to Word-Order

Recent research analyzing the sensitivity of natural language understand...
07/29/2021 ∙ by Louis Clouâtre, et al. ∙ 0 ∙ share

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Memory Augmented Optimizers for Deep Learning

Popular approaches for minimizing loss in data-driven learning often inv...
06/20/2021 ∙ by Paul-Aymeric McRae, et al. ∙ 0 ∙ share

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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...
06/20/2021 ∙ by Prasanna Parthasarathi, et al. ∙ 11 ∙ share

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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...
06/20/2021 ∙ by Prasanna Parthasarathi, et al. ∙ 6 ∙ share

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TAG: Task-based Accumulated Gradients for Lifelong learning

When an agent encounters a continual stream of new tasks in the lifelong...
05/11/2021 ∙ by Pranshu Malviya, et al. ∙ 0 ∙ share

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Continuous Coordination As a Realistic Scenario for Lifelong Learning

Current deep reinforcement learning (RL) algorithms are still highly tas...
03/04/2021 ∙ by Hadi Nekoei, et al. ∙ 0 ∙ share

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IIRC: Incremental Implicitly-Refined Classification

We introduce the "Incremental Implicitly-Refined Classi-fication (IIRC)"...
12/23/2020 ∙ by Mohamed Abdelsalam, et al. ∙ 7 ∙ share

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Maximum Reward Formulation In Reinforcement Learning

Reinforcement learning (RL) algorithms typically deal with maximizing th...
10/08/2020 ∙ by Sai Krishna Gottipati, et al. ∙ 23 ∙ share

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MLMLM: Link Prediction with Mean Likelihood Masked Language Model

Knowledge Bases (KBs) are easy to query, verifiable, and interpretable. ...
09/15/2020 ∙ by Louis Clouâtre, et al. ∙ 5 ∙ share

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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...
08/24/2020 ∙ by Prasanna Parthasarathi, et al. ∙ 11 ∙ share

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Slot Contrastive Networks: A Contrastive Approach for Representing Objects

Unsupervised extraction of objects from low-level visual data is an impo...
07/18/2020 ∙ by Evan Racah, et al. ∙ 6 ∙ share

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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...
07/07/2020 ∙ by Harm van Seijen, et al. ∙ 2 ∙ share

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PatchUp: A Regularization Technique for Convolutional Neural Networks

Large capacity deep learning models are often prone to a high generaliza...
06/14/2020 ∙ by Mojtaba Faramarzi, et al. ∙ 42 ∙ share

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Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning

Over the last decade, there has been significant progress in the field o...
04/26/2020 ∙ by Sai Krishna Gottipati, et al. ∙ 4 ∙ share

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Towards Lossless Encoding of Sentences

A lot of work has been done in the field of image compression via machin...
06/04/2019 ∙ by Gabriele Prato, et al. ∙ 0 ∙ share

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

Neural generative models have been become increasingly popular when buil...
06/04/2019 ∙ by Chinnadhurai Sankar, et al. ∙ 2 ∙ share

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Structure Learning for Neural Module Networks

Neural Module Networks, originally proposed for the task of visual quest...
05/27/2019 ∙ by Vardaan Pahuja, et al. ∙ 1 ∙ share

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Edge Replacement Grammars: A Formal Language Approach for Generating Graphs

Graphs are increasingly becoming ubiquitous as models for structured dat...
02/11/2019 ∙ by Revanth Reddy, et al. ∙ 0 ∙ share

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The Hanabi Challenge: A New Frontier for AI Research

From the early days of computing, games have been important testbeds for...
02/01/2019 ∙ by Nolan Bard, et al. ∙ 54 ∙ share

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Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies

Modelling long-term dependencies is a challenge for recurrent neural net...
01/22/2019 ∙ by Sarath Chandar, et al. ∙ 0 ∙ share

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Environments for Lifelong Reinforcement Learning

To achieve general artificial intelligence, reinforcement learning (RL) ...
11/26/2018 ∙ by Khimya Khetarpal, et al. ∙ 0 ∙ share

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On Training Recurrent Neural Networks for Lifelong Learning

Capacity saturation and catastrophic forgetting are the central challeng...
11/16/2018 ∙ by Shagun Sodhani, et al. ∙ 0 ∙ share

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Language Expansion In Text-Based Games

Text-based games are suitable test-beds for designing agents that can le...
05/17/2018 ∙ by Ghulam Ahmed Ansari, et al. ∙ 0 ∙ share

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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...
01/31/2018 ∙ by Amrita Saha, et al. ∙ 0 ∙ share

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A Deep Reinforcement Learning Chatbot (Short Version)

We present MILABOT: a deep reinforcement learning chatbot developed by t...
01/20/2018 ∙ by Iulian V. Serban, et al. ∙ 0 ∙ share

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A Deep Reinforcement Learning Chatbot

We present MILABOT: a deep reinforcement learning chatbot developed by t...
09/07/2017 ∙ by Iulian V. Serban, et al. ∙ 0 ∙ share

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Memory Augmented Neural Networks with Wormhole Connections

Recent empirical results on long-term dependency tasks have shown that n...
01/30/2017 ∙ by Caglar Gulcehre, et al. ∙ 0 ∙ share

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GuessWhat?! Visual object discovery through multi-modal dialogue

We introduce GuessWhat?!, a two-player guessing game as a testbed for re...
11/23/2016 ∙ by Harm de Vries, et al. ∙ 0 ∙ share

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Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes

We extend neural Turing machine (NTM) model into a dynamic neural Turing...
06/30/2016 ∙ by Caglar Gulcehre, et al. ∙ 0 ∙ share

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A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation

Interlingua based Machine Translation (MT) aims to encode multiple langu...
06/15/2016 ∙ by Amrita Saha, et al. ∙ 0 ∙ share

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Hierarchical Memory Networks

Memory networks are neural networks with an explicit memory component th...
05/24/2016 ∙ by Sarath Chandar, et al. ∙ 0 ∙ share

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Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus

Over the past decade, large-scale supervised learning corpora have enabl...
03/22/2016 ∙ by Iulian Vlad Serban, et al. ∙ 0 ∙ share

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Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning

Recently there has been a lot of interest in learning common representat...
10/13/2015 ∙ by Janarthanan Rajendran, et al. ∙ 0 ∙ share

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Reasoning about Linguistic Regularities in Word Embeddings using Matrix Manifolds

Recent work has explored methods for learning continuous vector space wo...
07/28/2015 ∙ by Sridhar Mahadevan, et al. ∙ 0 ∙ share

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Clustering is Efficient for Approximate Maximum Inner Product Search

Efficient Maximum Inner Product Search (MIPS) is an important task that ...
07/21/2015 ∙ by Alex Auvolat, et al. ∙ 0 ∙ share

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Correlational Neural Networks

Common Representation Learning (CRL), wherein different descriptions (or...
04/27/2015 ∙ by Sarath Chandar, et al. ∙ 0 ∙ share

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Sarath Chandar

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