Rishabh Iyer
Rishabh Iyer
Assistant Professor, University of Texas Dallas
Verified email at utdallas.edu - Homepage
Title
Cited by
Cited by
Year
Submodular optimization with submodular cover and submodular knapsack constraints
RK Iyer, JA Bilmes
Advances in Neural Information Processing Systems (NIPS), 2436-2444, 2013
1852013
Submodularity in data subset selection and active learning
K Wei, R Iyer, J Bilmes
International Conference on Machine Learning, 1954-1963, 2015
1592015
Learning mixtures of submodular functions for image collection summarization
S Tschiatschek, RK Iyer, H Wei, JA Bilmes
Advances in Neural Information Processing Systems (NIPS), 1413-1421, 2014
1522014
Algorithms for approximate minimization of the difference between submodular functions, with applications
R Iyer, J Bilmes
Uncertainty in Artificial Intelligence (UAI), 2012
1202012
Fast semidifferential-based submodular function optimization
R Iyer, S Jegelka, J Bilmes
International Conference on Machine Learning (ICML), 2013
112*2013
Curvature and optimal algorithms for learning and minimizing submodular functions
RK Iyer, S Jegelka, JA Bilmes
Advances in Neural Information Processing Systems (NIPS), 2742-2750, 2013
912013
Fast multi-stage submodular maximization
K Wei, R Iyer, J Bilmes
International Conference on Machine Learning (ICML-14), 1494-1502, 2014
702014
Submodular-Bregman and the Lovász-Bregman divergences with applications
R Iyer, JA Bilmes
Advances in Neural Information Processing Systems, 2933-2941, 2012
402012
Submodular-Bregman and the Lovasz-Bregman Divergences with Applications
R Iyer, J Bilmes
Advances in Neural Information Processing Systems (NIPS), 2942-2950, 2012
402012
Submodular Point Processes
R Iyer, J Bilmes
Proc. Artificial Intelligence and Statistics (AISTATS), 2015
26*2015
Mixed robust/average submodular partitioning: Fast algorithms, guarantees, and applications
K Wei, RK Iyer, S Wang, W Bai, JA Bilmes
Advances in Neural Information Processing Systems, 2233-2241, 2015
242015
Monotone closure of relaxed constraints in submodular optimization: Connections between minimization and maximization: Extended version
R Iyer, S Jegelka, J Bilmes
UAI, 2014
242014
The Lovász-Bregman Divergence and connections to rank aggregation, clustering, and web ranking
R Iyer, JA Bilmes
Uncertainty in Artificial Intelligence, 2014
212014
Algorithms for optimizing the ratio of submodular functions
W Bai, R Iyer, K Wei, J Bilmes
International Conference on Machine Learning, 2751-2759, 2016
202016
Polyhedral aspects of submodularity, convexity and concavity
R Iyer, J Bilmes
arXiv preprint arXiv:1506.07329, 2015
202015
Submodular hamming metrics
JA Gillenwater, RK Iyer, B Lusch, R Kidambi, JA Bilmes
Advances in Neural Information Processing Systems, 3141-3149, 2015
162015
Summarization of Multi-Document Topic Hierarchies using Submodular Mixtures
RB Bairi, R Iyer, G Ramakrishnan, J Bilmes
In Association of Computational Linguists (ACL) 2015, 2015
162015
Mirror descent like algorithms for submodular optimization
R Iyer, S Jegelka, J Bilmes
NIPS Workshop on Discrete Optimization in Machine Learning (DISCML), 2012
122012
Active machine learning
DM Chickering, CA Meek, PY Simard, RK Iyer
US Patent 10,262,272, 2019
102019
Submodular Optimization and Machine Learning: Theoretical Results, Unifying and Scalable Algorithms, and Applications
R Iyer
Ph.D Dissertation, 2015
102015
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