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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...
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07/31/2023
Lookbehind Optimizer: k steps back, 1 step forward
The Lookahead optimizer improves the training stability of deep neural n...
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07/18/2023
Promoting Exploration in Memory-Augmented Adam using Critical Momenta
Adaptive gradient-based optimizers, particularly Adam, have left their m...
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06/30/2023
Thompson sampling for improved exploration in GFlowNets
Generative flow networks (GFlowNets) are amortized variational inference...
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05/24/2023
Measuring the Knowledge Acquisition-Utilization Gap in Pretrained Language Models
While pre-trained language models (PLMs) have shown evidence of acquirin...
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05/22/2023
Should We Attend More or Less? Modulating Attention for Fairness
The abundance of annotated data in natural language processing (NLP) pos...
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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...
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03/16/2023
Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning
Efficient exploration is critical in cooperative deep Multi-Agent Reinfo...
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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...
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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)...
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11/20/2022
Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness
Data-driven predictive solutions predominant in commercial applications ...
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11/18/2022
Sharpness-Aware Training for Accurate Inference on Noisy DNN Accelerators
Energy-efficient deep neural network (DNN) accelerators are prone to non...
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11/09/2022
Local Structure Matters Most in Most Languages
Many recent perturbation studies have found unintuitive results on what ...
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11/09/2022
Detecting Languages Unintelligible to Multilingual Models through Local Structure Probes
Providing better language tools for low-resource and endangered language...
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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...
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08/03/2022
Improving Meta-Learning Generalization with Activation-Based Early-Stopping
Meta-Learning algorithms for few-shot learning aim to train neural netwo...
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07/10/2022
An Introduction to Lifelong Supervised Learning
This primer is an attempt to provide a detailed summary of the different...
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04/25/2022
Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
In recent years, a growing number of deep model-based reinforcement lear...
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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...
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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...
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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...
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08/10/2021
Post-hoc Interpretability for Neural NLP: A Survey
Natural Language Processing (NLP) models have become increasingly more c...
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07/29/2021
Demystifying Neural Language Models' Insensitivity to Word-Order
Recent research analyzing the sensitivity of natural language understand...
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06/20/2021
Memory Augmented Optimizers for Deep Learning
Popular approaches for minimizing loss in data-driven learning often inv...
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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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05/11/2021
TAG: Task-based Accumulated Gradients for Lifelong learning
When an agent encounters a continual stream of new tasks in the lifelong...
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03/04/2021
Continuous Coordination As a Realistic Scenario for Lifelong Learning
Current deep reinforcement learning (RL) algorithms are still highly tas...
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12/23/2020
IIRC: Incremental Implicitly-Refined Classification
We introduce the "Incremental Implicitly-Refined Classi-fication (IIRC)"...
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10/08/2020
Maximum Reward Formulation In Reinforcement Learning
Reinforcement learning (RL) algorithms typically deal with maximizing th...
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09/15/2020
MLMLM: Link Prediction with Mean Likelihood Masked Language Model
Knowledge Bases (KBs) are easy to query, verifiable, and interpretable. ...
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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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07/18/2020
Slot Contrastive Networks: A Contrastive Approach for Representing Objects
Unsupervised extraction of objects from low-level visual data is an impo...
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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...
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06/14/2020
PatchUp: A Regularization Technique for Convolutional Neural Networks
Large capacity deep learning models are often prone to a high generaliza...
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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...
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06/04/2019
Towards Lossless Encoding of Sentences
A lot of work has been done in the field of image compression via machin...
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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...
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05/27/2019
Structure Learning for Neural Module Networks
Neural Module Networks, originally proposed for the task of visual quest...
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02/11/2019
Edge Replacement Grammars: A Formal Language Approach for Generating Graphs
Graphs are increasingly becoming ubiquitous as models for structured dat...
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02/01/2019
The Hanabi Challenge: A New Frontier for AI Research
From the early days of computing, games have been important testbeds for...
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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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11/26/2018
Environments for Lifelong Reinforcement Learning
To achieve general artificial intelligence, reinforcement learning (RL) ...
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11/16/2018
On Training Recurrent Neural Networks for Lifelong Learning
Capacity saturation and catastrophic forgetting are the central challeng...
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05/17/2018
Language Expansion In Text-Based Games
Text-based games are suitable test-beds for designing agents that can le...
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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...
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01/20/2018
A Deep Reinforcement Learning Chatbot (Short Version)
We present MILABOT: a deep reinforcement learning chatbot developed by t...
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09/07/2017
A Deep Reinforcement Learning Chatbot
We present MILABOT: a deep reinforcement learning chatbot developed by t...
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01/30/2017
Memory Augmented Neural Networks with Wormhole Connections
Recent empirical results on long-term dependency tasks have shown that n...
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11/23/2016