Vikas K. Garg

Publication Activity (10 Years)

Years Active: 2009-2023
Publications (10 Years): 26

Top Topics

Supervised Learning

Top Venues

Publications

Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas K. Garg, Samuel Kaski, Tommi S. Jaakkola
Compositional Sculpting of Iterative Generative Processes. NeurIPS (2023)
Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas K. Garg, Samuel Kaski, Tommi S. Jaakkola
Compositional Sculpting of Iterative Generative Processes. CoRR (2023)
David Alvarez-Melis, Vikas K. Garg, Adam Kalai
Are GANs overkill for NLP? NeurIPS (2022)
David Alvarez-Melis, Vikas K. Garg, Adam Tauman Kalai
Why GANs are overkill for NLP. CoRR (2022)
Vikas K. Garg, Adam Tauman Kalai, Katrina Ligett, Zhiwei Steven Wu
Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization. AISTATS (2021)
Vikas K. Garg, Stefanie Jegelka, Tommi S. Jaakkola
Generalization and Representational Limits of Graph Neural Networks. CoRR (2020)
Vikas K. Garg, Tommi S. Jaakkola
Predicting deliberative outcomes. ICML (2020)
Vikas K. Garg, Adam Kalai, Katrina Ligett, Zhiwei Steven Wu
Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization. CoRR (2020)
Vikas K. Garg, Stefanie Jegelka, Tommi S. Jaakkola
Generalization and Representational Limits of Graph Neural Networks. ICML (2020)
Vikas K. Garg, Tommi S. Jaakkola
Solving graph compression via optimal transport. CoRR (2019)
Vikas K. Garg, Tamar Pichkhadze
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms. NeurIPS (2019)
Vikas K. Garg, Tommi S. Jaakkola
Solving graph compression via optimal transport. NeurIPS (2019)
John Ingraham, Vikas K. Garg, Regina Barzilay, Tommi S. Jaakkola
Generative Models for Graph-Based Protein Design. DGS@ICLR (2019)
Vikas K. Garg, Tommi S. Jaakkola
Strategic Prediction with Latent Aggregative Games. CoRR (2019)
Vikas K. Garg, Inderjit S. Dhillon, Hsiang-Fu Yu
Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure. CoRR (2019)
John Ingraham, Vikas K. Garg, Regina Barzilay, Tommi S. Jaakkola
Generative Models for Graph-Based Protein Design. NeurIPS (2019)
Vikas K. Garg, Lin Xiao, Ofer Dekel
Sparse Multi-Prototype Classification. UAI (2018)
Vikas K. Garg, Tamar Pichkhadze
Peek Search: Near-Optimal Online Markov Decoding. CoRR (2018)
Vikas K. Garg, Ofer Dekel, Lin Xiao
Learning SMaLL Predictors. NeurIPS (2018)
Vikas K. Garg
Supervising Unsupervised Learning. NeurIPS (2018)
Vikas K. Garg, Ofer Dekel, Lin Xiao
Learning SMaLL Predictors. CoRR (2018)
Vikas K. Garg, Tommi S. Jaakkola
Local Aggregative Games. NIPS (2017)
Vikas K. Garg, Adam Kalai
Supervising Unsupervised Learning. CoRR (2017)
Vikas K. Garg, Cynthia Rudin, Tommi S. Jaakkola
CRAFT: ClusteR-specific Assorted Feature selecTion. AISTATS (2016)
Vikas K. Garg, Adam Tauman Kalai
Meta-Unsupervised-Learning: A supervised approach to unsupervised learning. CoRR (2016)
Vikas K. Garg, Tommi S. Jaakkola
Learning Tree Structured Potential Games. NIPS (2016)
Sukrit Shankar, Vikas K. Garg, Roberto Cipolla
DEEP-CARVING: Discovering Visual Attributes by Carving Deep Neural Nets. CoRR (2015)
Vikas K. Garg, Cynthia Rudin, Tommi S. Jaakkola
CRAFT: ClusteR-specific Assorted Feature selecTion. CoRR (2015)
Sukrit Shankar, Vikas K. Garg, Roberto Cipolla
DEEP-CARVING: Discovering visual attributes by carving deep neural nets. CVPR (2015)
Risi Kondor, Nedelina Teneva, Vikas K. Garg
Multiresolution Matrix Factorization. ICML (2014)
Priyanka Agrawal, Vikas K. Garg, Ramasuri Narayanam
Link Label Prediction in Signed Social Networks. IJCAI (2013)
Vikas K. Garg, Y. Narahari, M. Narasimha Murty
Novel Biobjective Clustering (BiGC) Based on Cooperative Game Theory. IEEE Trans. Knowl. Data Eng. 25 (5) (2013)
Vikas K. Garg, T. S. Jayram, Balakrishnan Narayanaswamy
Online Optimization with Dynamic Temporal Uncertainty: Incorporating Short Term Predictions for Renewable Integration in Intelligent Energy Systems. AAAI (2013)
Samory Kpotufe, Vikas K. Garg
Adaptivity to Local Smoothness and Dimension in Kernel Regression. NIPS (2013)
Vikas K. Garg, Sneha Chaudhari, Ankur Narang
Multi-regularization for Fuzzy Co-clustering. ICONIP (2) (2013)
Balakrishnan Narayanaswamy, Vikas K. Garg, T. S. Jayram
Prediction based storage management in the smart grid. SmartGridComm (2012)
Balakrishnan Narayanaswamy, Vikas K. Garg, T. S. Jayram
Online optimization for the smart (micro) grid. e-Energy (2012)
Souvik Bhattacherjee, Ankur Narang, Vikas K. Garg
High throughput data redundancy removal algorithm with scalable performance. HiPEAC (2011)
Vikas K. Garg, Ankur Narang, Souvik Bhattacherjee
Real-time memory efficient data redundancy removal algorithm. CIKM (2010)
Ankur Narang, Raj Gupta, Anupam Joshi, Vikas K. Garg
Highly scalable parallel collaborative filtering algorithm. HiPC (2010)
Vikas K. Garg, Nukala Viswanadham
EcoSupply: A Machine Learning Framework for Analyzing the Impact of Ecosystem on Global Supply Chain Dynamics. SEAL (2010)
Vikas K. Garg, M. Narasimha Murty
EPIC: Efficient Integration of Partitional Clustering Algorithms for Classification. SEAL (2010)
Vikas K. Garg
Toward Optimal Disk Layout of Genome Scale Suffix Trees. SEAL (2010)
Vikas K. Garg, M. Narasimha Murty
RACK: RApid clustering using K-means algorithm. CASE (2009)
Vikas K. Garg, M. Narasimha Murty
Feature subspace SVMs (FS-SVMs) for high dimensional handwritten digit recognition. Int. J. Data Min. Model. Manag. 1 (4) (2009)