Vikas K. Garg

45 papers A* 13A 5Misc 1Journal 14Unranked 12
YearRankTypeTitle / Venue / Authors
2025 A* conf
Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models.
ICML
Rafal Karczewski, Markus Heinonen, Vikas K. Garg
2025 J jnl
Heterophily-informed Message Passing.
Trans. Mach. Learn. Res.
Haishan Wang, Arno Solin, Vikas K. Garg
2025 A* conf
Positional Encoding meets Persistent Homology on Graphs.
ICML
Yogesh Verma, Amauri H. Souza, Vikas K. Garg
2025 A conf
What Ails Generative Structure-based Drug Design: Expressivity is Too Little or Too Much?
AISTATS
Rafal Karczewski, Samuel Kaski, Markus Heinonen, Vikas K. Garg
2021 A conf
Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization.
AISTATS
Vikas K. Garg, Adam Tauman Kalai, Katrina Ligett, Zhiwei Steven Wu
2020 A* conf
Generalization and Representational Limits of Graph Neural Networks.
ICML
Vikas K. Garg, Stefanie Jegelka, Tommi S. Jaakkola
2020 J jnl
Generalization and Representational Limits of Graph Neural Networks.
CoRR
Vikas K. Garg, Stefanie Jegelka, Tommi S. Jaakkola
2020 J jnl
Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization.
CoRR
Vikas K. Garg, Adam Kalai, Katrina Ligett, Zhiwei Steven Wu
2020 A* conf
Predicting deliberative outcomes.
ICML
Vikas K. Garg, Tommi S. Jaakkola
2019 — conf
Generative Models for Graph-Based Protein Design.
DGS@ICLR
John Ingraham, Vikas K. Garg, Regina Barzilay, Tommi S. Jaakkola
2019 A* conf
Generative Models for Graph-Based Protein Design.
NeurIPS
John Ingraham, Vikas K. Garg, Regina Barzilay, Tommi S. Jaakkola
2019 J jnl
Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure.
CoRR
Vikas K. Garg, Inderjit S. Dhillon, Hsiang-Fu Yu
2019 A* conf
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms.
NeurIPS
Vikas K. Garg, Tamar Pichkhadze
2019 A* conf
Solving graph compression via optimal transport.
NeurIPS
Vikas K. Garg, Tommi S. Jaakkola
2019 J jnl
Solving graph compression via optimal transport.
CoRR
Vikas K. Garg, Tommi S. Jaakkola
2019 J jnl
Strategic Prediction with Latent Aggregative Games.
CoRR
Vikas K. Garg, Tommi S. Jaakkola
2018 A* conf
Learning SMaLL Predictors.
NeurIPS
Vikas K. Garg, Ofer Dekel, Lin Xiao
2018 J jnl
Learning SMaLL Predictors.
CoRR
Vikas K. Garg, Ofer Dekel, Lin Xiao
2018 J jnl
Peek Search: Near-Optimal Online Markov Decoding.
CoRR
Vikas K. Garg, Tamar Pichkhadze
2018 A conf
Sparse Multi-Prototype Classification.
UAI
Vikas K. Garg, Lin Xiao, Ofer Dekel
2018 A* conf
Supervising Unsupervised Learning.
NeurIPS
Vikas K. Garg
2017 — conf
Local Aggregative Games.
NIPS
Vikas K. Garg, Tommi S. Jaakkola
2017 J jnl
Supervising Unsupervised Learning.
CoRR
Vikas K. Garg, Adam Kalai
2016 A conf
CRAFT: ClusteR-specific Assorted Feature selecTion.
AISTATS
Vikas K. Garg, Cynthia Rudin, Tommi S. Jaakkola
2016 — conf
Learning Tree Structured Potential Games.
NIPS
Vikas K. Garg, Tommi S. Jaakkola
2016 J jnl
Meta-Unsupervised-Learning: A supervised approach to unsupervised learning.
CoRR
Vikas K. Garg, Adam Tauman Kalai
2015 J jnl
CRAFT: ClusteR-specific Assorted Feature selecTion.
CoRR
Vikas K. Garg, Cynthia Rudin, Tommi S. Jaakkola
2015 J jnl
DEEP-CARVING: Discovering Visual Attributes by Carving Deep Neural Nets.
CoRR
Sukrit Shankar, Vikas K. Garg, Roberto Cipolla
2015 A* conf
DEEP-CARVING: Discovering visual attributes by carving deep neural nets.
CVPR
Sukrit Shankar, Vikas K. Garg, Roberto Cipolla
2014 A* conf
Multiresolution Matrix Factorization.
ICML
Risi Kondor, Nedelina Teneva, Vikas K. Garg
2013 — conf
Adaptivity to Local Smoothness and Dimension in Kernel Regression.
NIPS
Samory Kpotufe, Vikas K. Garg
2013 A* conf
Link Label Prediction in Signed Social Networks.
IJCAI
Priyanka Agrawal, Vikas K. Garg, Ramasuri Narayanam
2013 — conf
Multi-regularization for Fuzzy Co-clustering.
ICONIP (2)
Vikas K. Garg, Sneha Chaudhari, Ankur Narang
2013 J jnl
Novel Biobjective Clustering (BiGC) Based on Cooperative Game Theory.
IEEE Trans. Knowl. Data Eng.
Vikas K. Garg, Y. Narahari, M. Narasimha Murty
2013 A* conf
Online Optimization with Dynamic Temporal Uncertainty: Incorporating Short Term Predictions for Renewable Integration in Intelligent Energy Systems.
AAAI
Vikas K. Garg, T. S. Jayram, Balakrishnan Narayanaswamy
2012 — conf
Online optimization for the smart (micro) grid.
e-Energy
Balakrishnan Narayanaswamy, Vikas K. Garg, T. S. Jayram
2012 — conf
Prediction based storage management in the smart grid.
SmartGridComm
Balakrishnan Narayanaswamy, Vikas K. Garg, T. S. Jayram
2011 — conf
High throughput data redundancy removal algorithm with scalable performance.
HiPEAC
Souvik Bhattacherjee, Ankur Narang, Vikas K. Garg
2010 — conf
EPIC: Efficient Integration of Partitional Clustering Algorithms for Classification.
SEAL
Vikas K. Garg, M. Narasimha Murty
2010 — conf
EcoSupply: A Machine Learning Framework for Analyzing the Impact of Ecosystem on Global Supply Chain Dynamics.
SEAL
Vikas K. Garg, Nukala Viswanadham
2010 Misc conf
Highly scalable parallel collaborative filtering algorithm.
HiPC
Ankur Narang, Raj Gupta, Anupam Joshi, Vikas K. Garg
2010 A conf
Real-time memory efficient data redundancy removal algorithm.
CIKM
Vikas K. Garg, Ankur Narang, Souvik Bhattacherjee
2010 — conf
Toward Optimal Disk Layout of Genome Scale Suffix Trees.
SEAL
Vikas K. Garg
2009 J jnl
Feature subspace SVMs (FS-SVMs) for high dimensional handwritten digit recognition.
Int. J. Data Min. Model. Manag.
Vikas K. Garg, M. Narasimha Murty
2009 — conf
RACK: RApid clustering using K-means algorithm.
CASE
Vikas K. Garg, M. Narasimha Murty