Avishek Saha

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Hal Daumé IIIAssociate Professor of Computer Science, University of MarylandVerified email at umiacs.umd.edu
Suresh VenkatasubramanianBrown UniversityVerified email at brown.edu
Piyush RaiIIT KanpurVerified email at cse.iitk.ac.in
Shamik SuralProfessor, Dept. of Computer Science & Engineering, Indian Institute of Technology, Kharagpur, IndiaVerified email at cse.iitkgp.ac.in
Divesh SrivastavaAT&T Labs-ResearchVerified email at research.att.com
Abhishek KumarGoogle BrainVerified email at google.com
Valerio PascucciEndowed Chair professor and Director of the Center for Extreme Data Management Analysis andVerified email at sci.utah.edu
Hua OuyangMachine Learning Research Manager, Apple AI/MLVerified email at gatech.edu
Howard KarloffGoldman SachsVerified email at cc.gatech.edu
Makoto YamadaOIST & FlatMinima Inc.Verified email at oist.jp
Dawei YinSenior Director of Search Science at Baidu, Inc.Verified email at baidu.com
Jeff PhillipsProfessor, School of Computing, University of UtahVerified email at cs.utah.edu
Nick KoudasProfessor of Computer Science, University of TorontoVerified email at cs.toronto.edu
Scott L. DuVallDepartment of Veterans Affairs and Epidemiology, University of Utah School of MedicineVerified email at utah.edu
Peer-Timo BremerLawrence Livermore National LaboratoryVerified email at llnl.gov
Filippo MenczerLuddy Distinguished Professor of Informatics and Computer Science, Indiana UniversityVerified email at indiana.edu
Jiliang TangUniversity Foundation Professor of Computer Science and Engineering, Michigan State UniversityVerified email at msu.edu
Andrei IrimiaAssociate Professor, USC & KCLVerified email at usc.edu
Marcel PrastawaIcahn School of Medicine at Mount SinaiVerified email at mssm.edu
Guido GerigNYU Tandon School of Engineering, CSE DepartmentVerified email at nyu.edu

Avishek Saha

Machine Learning Scientist, Amazon

Verified email at amazon.com

Machine Learning


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Frustratingly easy semi-supervised domain adaptation H Daumé III, A Kumar, A Saha Proceedings of the 2010 Workshop on Domain Adaptation for Natural Language …, 2010	242	2010
Co-regularization based semi-supervised domain adaptation A Kumar, A Saha, H Daume Advances in neural information processing systems 23, 2010	220	2010
Domain adaptation meets active learning P Rai, A Saha, H Daumé III, S Venkatasubramanian Proceedings of the NAACL HLT 2010 Workshop on Active Learning for Natural …, 2010	187	2010
Sequential dependencies L Golab, H Karloff, F Korn, A Saha, D Srivastava Proceedings of the VLDB Endowment 2 (1), 574-585, 2009	152	2009
Online Learning of Multiple Tasks and Their Relationships A Saha, P Rai, H Daumé III, S Venkatasubramanian update 1 (1), 2, 0	135*
Metric functional dependencies N Koudas, A Saha, D Srivastava, S Venkatasubramanian 2009 IEEE 25th International Conference on Data Engineering, 1275-1278, 2009	130	2009
Active supervised domain adaptation A Saha, P Rai, H Daumé, S Venkatasubramanian, SL DuVall Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011	112	2011
Ultra high-dimensional nonlinear feature selection for big biological data M Yamada, J Tang, J Lugo-Martinez, E Hodzic, R Shrestha, A Saha, ... IEEE Transactions on Knowledge and Data Engineering 30 (7), 1352-1365, 2018	89	2018
New pixel-decimation patterns for block matching in motion estimation A Saha, J Mukherjee, S Sural Signal Processing: Image Communication 23 (10), 725-738, 2008	60	2008
A neighborhood elimination approach for block matching in motion estimation A Saha, J Mukherjee, S Sural Signal Processing: Image Communication 26 (8-9), 438-454, 2011	49	2011
Efficient protocols for distributed classification and optimization H Daumé, JM Phillips, A Saha, S Venkatasubramanian Algorithmic Learning Theory: 23rd International Conference, ALT 2012, Lyon …, 2012	47	2012
Characterization and Modeling of PIDX Parallel I/O for Performance Optimization S Kumar, A Saha, V Vishwanath Conference on High Performance Computing Networking, Storage and Analysis, 2013	40	2013
Protocols for learning classifiers on distributed data H Daume III, J Phillips, A Saha, S Venkatasubramanian Artificial Intelligence and Statistics, 282-290, 2012	33	2012
SKIP prediction for fast rate distortion optimization in H. 264 A Saha, K Mallick, J Mukherjee, S Sural IEEE Transactions on Consumer Electronics 53 (3), 1153-1160, 2007	29	2007
Modeling 4D changes in pathological anatomy using domain adaptation: Analysis of TBI imaging using a tumor database B Wang, M Prastawa, A Saha, SP Awate, A Irimia, MC Chambers, ... Multimodal Brain Image Analysis: Third International Workshop, MBIA 2013 …, 2013	12	2013
HD III, and S. Venkatasubramanian A Saha, P Rai Online learning of multiple tasks and their relationships. In AISTATS, 2011	12	2011
: N-dimensional data analysis and visualization analysis for the National Ignition Campaign PT Bremer, D Maljovec, A Saha, B Wang, J Gaffney, BK Spears, ... Computing and Visualization in Science 17, 1-18, 2015	11	2015
A comparative study of morse complex approximation using different neighborhood graphs D Maljovec, A Saha, P Lindstrom, PT Bremer, B Wang, C Correa, ... Workshop on Topological Methods in Data Analysis and Visualization (accepted), 2013	11	2013
Active online multitask learning A Saha, P Rai, H Daumé III, S Venkatasubramanian ICML 2010 Workshop on Budget Learning, 2010	10	2010
Processing data using sequential dependencies L Golab, H Karloff, P Korn, D Srivastava, A Saha US Patent 8,645,309, 2014	9	2014

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