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06/25/2023
PolicyClusterGCN: Identifying Efficient Clusters for Training Graph Convolutional Networks
Graph convolutional networks (GCNs) have achieved huge success in severa...
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05/30/2023
GAN-MPC: Training Model Predictive Controllers with Parameterized Cost Functions using Demonstrations from Non-identical Experts
Model predictive control (MPC) is a popular approach for trajectory opti...
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05/23/2023
Clustering Indices based Automatic Classification Model Selection
Classification model selection is a process of identifying a suitable mo...
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04/12/2023
Bi-level Latent Variable Model for Sample-Efficient Multi-Agent Reinforcement Learning
Despite their potential in real-world applications, multi-agent reinforc...
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03/13/2023
Are Models Trained on Indian Legal Data Fair?
Recent advances and applications of language technology and artificial i...
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12/05/2022
Physics-Informed Model-Based Reinforcement Learning
We apply reinforcement learning (RL) to robotics. One of the drawbacks o...
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11/27/2022
ReGrAt: Regularization in Graphs using Attention to handle class imbalance
Node classification is an important task to solve in graph-based learnin...
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07/14/2022
GrabQC: Graph based Query Contextualization for automated ICD coding
Automated medical coding is a process of codifying clinical notes to app...
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06/25/2022
Multi-Variate Time Series Forecasting on Variable Subsets
We formulate a new inference task in the domain of multivariate time ser...
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06/12/2022
Matching options to tasks using Option-Indexed Hierarchical Reinforcement Learning
The options framework in Hierarchical Reinforcement Learning breaks down...
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04/29/2022
Evolutionary Approach to Security Games with Signaling
Green Security Games have become a popular way to model scenarios involv...
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03/12/2022
A Survey in Adversarial Defences and Robustness in NLP
In recent years, it has been seen that deep neural networks are lacking ...
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11/29/2021
A Causal Approach for Unfair Edge Prioritization and Discrimination Removal
In budget-constrained settings aimed at mitigating unfairness, like law ...
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11/03/2021
Smooth Imitation Learning via Smooth Costs and Smooth Policies
Imitation learning (IL) is a popular approach in the continuous control ...
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10/15/2021
Dynamic probabilistic logic models for effective abstractions in RL
State abstraction enables sample-efficient learning and better task tran...
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10/15/2021
Multi-Tailed, Multi-Headed, Spatial Dynamic Memory refined Text-to-Image Synthesis
Synthesizing high-quality, realistic images from text-descriptions is a ...
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10/05/2021
Semi-Supervised Deep Learning for Multiplex Networks
Multiplex networks are complex graph structures in which a set of entiti...
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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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02/06/2021
Hyperedge Prediction using Tensor Eigenvalue Decomposition
Link prediction in graphs is studied by modeling the dyadic interactions...
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01/07/2021
qRRT: Quality-Biased Incremental RRT for Optimal Motion Planning in Non-Holonomic Systems
This paper presents a sampling-based method for optimal motion planning ...
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01/07/2021
Neural Fitted Q Iteration based Optimal Bidding Strategy in Real Time Reactive Power Market_1
In real time electricity markets, the objective of generation companies ...
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12/18/2020
Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty
Green Security Games (GSGs) have been successfully used in the protectio...
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12/16/2020
Relational Boosted Bandits
Contextual bandits algorithms have become essential in real-world user i...
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11/16/2020
Hypergraph Partitioning using Tensor Eigenvalue Decomposition
Hypergraphs have gained increasing attention in the machine learning com...
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10/30/2020
Goal directed molecule generation using Monte Carlo Tree Search
One challenging and essential task in biochemistry is the generation of ...
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08/18/2020
Reinforcement Learning for Improving Object Detection
The performance of a trained object detection neural network depends a l...
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07/10/2020
A Causal Linear Model to Quantify Edge Unfairness for Unfair Edge Prioritization and Discrimination Removal
The dataset can be generated by an unfair mechanism in numerous settings...
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06/07/2020
Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains
This paper describes the application of reinforcement learning (RL) to m...
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05/28/2020
On Incorporating Structural Information to improve Dialogue Response Generation
We consider the task of generating dialogue responses from background kn...
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05/09/2020
Understanding Dynamic Scenes using Graph Convolution Networks
We present a novel Multi Relational Graph Convolutional Network (MRGCN) ...
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04/29/2020
Towards Transparent and Explainable Attention Models
Recent studies on interpretability of attention distributions have led t...
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04/21/2020
EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks
Ensuring robustness of Deep Neural Networks (DNNs) is crucial to their a...
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02/03/2020
Towards Accurate Vehicle Behaviour Classification With Multi-Relational Graph Convolutional Networks
Understanding on-road vehicle behaviour from a temporal sequence of sens...
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01/15/2020
SEERL: Sample Efficient Ensemble Reinforcement Learning
Ensemble learning is a very prevalent method employed in machine learnin...
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10/01/2019
Reinforcement Learning for Multi-Objective Optimization of Online Decisions in High-Dimensional Systems
This paper describes a purely data-driven solution to a class of sequent...
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09/09/2019
Option Encoder: A Framework for Discovering a Policy Basis in Reinforcement Learning
Option discovery and skill acquisition frameworks are integral to the fu...
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08/31/2019
Let's Ask Again: Refine Network for Automatic Question Generation
In this work, we focus on the task of Automatic Question Generation (AQG...
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06/27/2019
ExTra: Transfer-guided Exploration
In this work we present a novel approach for transfer-guided exploration...
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06/17/2019
Learning Interpretable Models Using an Oracle
As Machine Learning (ML) becomes pervasive in various real world systems...
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05/17/2019
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning
Shaping in humans and animals has been shown to be a powerful tool for l...
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05/14/2019
Successor Options: An Option Discovery Framework for Reinforcement Learning
The options framework in reinforcement learning models the notion of a s...
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05/04/2019
Optimal Resampling for Learning Small Models
Models often need to be constrained to a certain size for them to be con...
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05/02/2019
Network Representation Learning: Consolidation and Renewed Bearing
Graphs are a natural abstraction for many problems where nodes represent...
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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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02/05/2019
Polyphonic Music Composition with LSTM Neural Networks and Reinforcement Learning
In the domain of algorithmic music composition, machine learning-driven ...
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01/01/2019
An Active Learning Framework for Efficient Robust Policy Search
Robust Policy Search is the problem of learning policies that do not deg...
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12/28/2018
Hypergraph Clustering: A Modularity Maximization Approach
Clustering on hypergraphs has been garnering increased attention with po...
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12/26/2018
Studying the Plasticity in Deep Convolutional Neural Networks using Random Pruning
Recently there has been a lot of work on pruning filters from deep convo...
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12/23/2018
Learning to Prevent Monocular SLAM Failure using Reinforcement Learning
Monocular SLAM refers to using a single camera to estimate robot ego mot...
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12/01/2018
