Balaraman Ravindran
Identifiers
No identifiers captured yet.
Papers (36)
- Generalized Random Surfer-Pair Models cs.SI · 2019 · author #2
- MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning cs.LG · 2019 · author #3
- Successor Options: An Option Discovery Framework for Reinforcement Learning cs.LG · 2019 · author #3
- Network Representation Learning: Consolidation and Renewed Bearing cs.LG · 2019 · author #11
- Edge Replacement Grammars: A Formal Language Approach for Generating Graphs cs.SI · 2019 · author #3
- Polyphonic Music Composition with LSTM Neural Networks and Reinforcement Learning cs.SD · 2019 · author #2
- Hypergraph Clustering: A Modularity Maximization Approach cs.LG · 2018 · author #5
- Studying the Plasticity in Deep Convolutional Neural Networks using Random Pruning cs.LG · 2018 · author #4
- Improvements on Hindsight Learning cs.LG · 2018 · author #4
- Fusion Graph Convolutional Networks cs.LG · 2018 · author #5
- HOPF: Higher Order Propagation Framework for Deep Collective Classification cs.LG · 2018 · author #5
- Language Expansion In Text-Based Games cs.CL · 2018 · author #4
- DiGrad: Multi-Task Reinforcement Learning with Shared Actions cs.LG · 2018 · author #5
- Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks cs.CV · 2018 · author #4
- Rate of Change Analysis for Interestingness Measures cs.LG · 2017 · author #4
- Efficient-UCBV: An Almost Optimal Algorithm using Variance Estimates cs.LG · 2017 · author #4
- Shared Learning : Enhancing Reinforcement in $Q$-Ensembles cs.LG · 2017 · author #2
- RAIL: Risk-Averse Imitation Learning cs.LG · 2017 · author #3
- Learning to Mix n-Step Returns: Generalizing lambda-Returns for Deep Reinforcement Learning cs.LG · 2017 · author #4
- Learning to Factor Policies and Action-Value Functions: Factored Action Space Representations for Deep Reinforcement learning cs.LG · 2017 · author #4
- Diversity driven Attention Model for Query-based Abstractive Summarization cs.CL · 2017 · author #4
- Thresholding Bandits with Augmented UCB cs.LG · 2017 · author #4
- DyVEDeep: Dynamic Variable Effort Deep Neural Networks cs.NE · 2017 · author #3
- Learning to Multi-Task by Active Sampling cs.NE · 2017 · author #4
- Exploration for Multi-task Reinforcement Learning with Deep Generative Models cs.AI · 2016 · author #3
- EPOpt: Learning Robust Neural Network Policies Using Model Ensembles cs.LG · 2016 · author #3
- HEMI: Hyperedge Majority Influence Maximization cs.SI · 2016 · author #2
- Linear Bandit algorithms using the Bootstrap stat.ML · 2016 · author #2
- Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning cs.CL · 2015 · author #4
- TSEB: More Efficient Thompson Sampling for Policy Learning cs.LG · 2015 · author #3
- A Reinforcement Learning Approach to Online Learning of Decision Trees cs.LG · 2015 · author #4
- Correlational Neural Networks cs.CL · 2015 · author #4
- Scalable Positional Analysis for Studying Evolution of Nodes in Networks cs.SI · 2014 · author #2
- An Autoencoder Approach to Learning Bilingual Word Representations cs.CL · 2014 · author #5
- Efficient Computation of the Shapley Value for Game-Theoretic Network Centrality cs.GT · 2014 · author #4
- Fractional Moments on Bandit Problems cs.LG · 2012 · author #2
Mentions
No mention provenance yet.
Frequent Coauthors
- Mitesh M. Khapra 7 shared papers
- Sarath Chandar 5 shared papers
- Nandan Sudarsanam 4 shared papers
- Srinivasan Parthasarathy 4 shared papers
- Priyesh Vijayan 3 shared papers
- Sahil Sharma 3 shared papers
- Ashutosh Jha 2 shared papers
- Deepak Mittal 2 shared papers
- Hugo Larochelle 2 shared papers
- K. P. Naveen 2 shared papers
- Manan Tomar 2 shared papers
- Rahul Ramesh 2 shared papers
- Shweta Bhardwaj 2 shared papers
- Subhojyoti Mukherjee 2 shared papers
- Yash Chandak 2 shared papers
- Aakash Srinivasan 1 shared papers
- Abhinav Garlapati 1 shared papers
- Abhishek Naik 1 shared papers
- Abhishek Sarkar 1 shared papers
- Abhishek Sharma 1 shared papers