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Talks
The list below gives links to posters, slides for some talks and lectures.
Invited Talks
DECAF: Deep Extreme Classification with Label Features,
Amazon Research Days, Virtual Event, December 16 – 17, 2020.
[pptx-slides]
Beyond Convenience: Beyond Convexity,
Mini Symposium on Computation and Optimization in the Sciences and Engineering, IIT Kanpur, February 3-4, 2016.
[pdf-slides]
An Introduction to Concentration Inequalities and Statistical Learning Theory,
MSR India Summer School 2015 on Machine Learning, June 15-26, 2015.
[pptx-slides]
Algorithms for Processing Massive Data Sets,
3rd International Symposium, Graduate School of Information, Production and Systems, Waseda University, Japan, March 10-11, 2010.
[pdf-slides]
Support Vector Machines and their Applications,
Summer School on Expert Systems and Their Applications, Indian Institute of Information Technology, Allahabad, June 10-14, 2009.
[pdf-slides]
Contributed Talks
Surrogate Functions for Maximizing Precision at the Top,
32nd International Conference on Machine Learning (ICML), Lille, France, July 6-11, 2015.
[pptx-slides]
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions,
30th International Conference on Machine Learning (ICML), Atlanta, Georgia, USA, June 16-21, 2013.
[pdf-slides]
On Low Distortion Embeddings of Statistical Distance Measures into Low Dimensional Spaces,
20th International Conference on Database and Expert Systems Applications (DEXA), Linz, Austria, August 31-September 4, 2009.
[pdf-slides]
Semantic Structure of the Indian Sign Language,
Eighth International Conference on South Asian Languages (ICOSAL), Aligarh Muslim University, January 6, 2008.
[pdf-slides]
INGIT: Limited Domain Formulaic Translation from Hindi to Indian Sign Language,
5th International Conference on Natural Language Processing (ICON), IIT Hyderabad, January 4-6, 2007.
[pdf-slides]
Spoken and Sign Languages: A Cross-modal Study,
Twenty Eighth All India Conference of Linguists (AICL), Banaras Hindu University, November 2-4, 2006.
[pdf-slides]
Posters
Sparse Local Embeddings for Extreme Multi-label Classification,
29th Annual Conference on Neural Information Processing Systems (NIPS), 2015.
(prepared by Kush Bhatia and Himanshu Jain)
[poster]
Robust Regression via Hard Thresholding,
29th Annual Conference on Neural Information Processing Systems (NIPS), 2015.
(prepared jointly with Kush Bhatia)
[poster]
Robust Regression,
6th Indo-American Symposium on Frontiers of Science (IAOFS), 2015.
[poster]
Surrogate Functions for Maximizing Precision at the Top,
32nd International Conference on Machine Learning (ICML), 2015.
[poster]
Optimizing Non-decomposable Performance Measures: A Tale of Two Classes,
32nd International Conference on Machine Learning (ICML), 2015.
(prepared by Harikrishna Narasimhan)
[poster]
Online and Stochastic Gradient Methods for Non-decomposable Loss Functions,
28th Annual Conference on Neural Information Processing Systems (NIPS), 2014.
[poster]
On Iterative Hard Thresholding Methods for High-dimensional M-Estimation,
28th Annual Conference on Neural Information Processing Systems (NIPS), 2014.
[poster]
Large-scale Multi-label Learning with Missing Labels,
31st International Conference on Machine Learning (ICML), 2014.
(prepared by Hsiang-Fu Yu)
[poster]
On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions,
30th International Conference on Machine Learning (ICML), 2013.
[poster]
Supervised Learning with Similarity Functions,
26th Annual Conference on Neural Information Processing Systems (NIPS), 2012.
[poster]
Random Feature Maps for Dot Product Kernels,
15th International Conference on Artificial Intelligence and Statistics (AISTATS), 2012.
[poster]
Similarity-based Learning via Data driven Embeddings,
25th Annual Conference on Neural Information Processing Systems (NIPS), 2011.
[poster]
Random Projection Trees Revisited,
24th Annual Conference on Neural Information Processing Systems (NIPS), 2010.
[poster]
Lectures, Seminars
Some Recent Advances in Non-convex Optimization,
Amazon Machine Learning Group, Bangalore, June 20, 2016.
The Data Science Institute, Columbia University, July 20, 2016.
[pdf-slides]
Extreme Classification - a Tale of Two Approaches,
Amazon Machine Learning Group, Bangalore, June 20, 2016.
Learning with Pairwise Losses,
Course Lecture for E0 370: Statistical Learning Theory, October 29, 2013.
(Instructor: Prof. Shivani Agarwal, Dept. of CSA, IISc)
[pdf-slides]
Online Learning with Pairwise Loss Functions,
MLSIG Seminar Series, Dept. of CSA, IISc, September 12, 2013.
[pdf-slides]
A pre-Weekend Talk on Online Learning,
TGIF Talk Series, Microsoft Research India, August 23, 2013.
[pdf-slides]
Explicit Feature Methods for Accelerated Kernel Learning,
Machine Learning and Optimization Group, Microsoft Research India, August 14, 2013.
[pdf-slides]
Accelerated Kernel Learning,
Department of CSE, IIT Gandhinagar, November 27, 2012.
[pdf-slides]
Topics in Kernel Learning,
Alan Turing Centenary Year Celebrations, Department of CSE, IIT Kanpur, October 10, 2012.
[pdf-slides]
Random Features for Kernel Learning,
Mysore Park Wokshop on Machine Learning, Infosys Campus Mysore, August 3, 2012.
[pdf-slides]
Learning with Similarity Functions,
Machine Learning and Optimization Group, Microsoft Research India, July 18, 2012.
[pdf-slides]
Similarity-based Learning via Data Driven Embeddings,
CSE Departmental Colloquia, CSE/IITK, October 28, 2011.
[pdf-slides]
Learning in Indefiniteness,
A presentation I gave for my PhD State of the Art seminar, CSE/IITK, August 2, 2010.
[pdf-slides]
An Introduction to Computational Learning Theory,
SIGML Seminar Series, CSE/IITK, January 23, 2010.
[pdf-slides]
How to Hoodwink a Halfspace,
A presentation I gave for my PhD comprehensive examination, CSE/IITK, January 12, 2010.
[pdf-slides]
Metric Embeddings and Applications in Computer Science,
SIGTACS Seminar Series, CSE/IITK, January 10, 2009.
[pdf-slides]
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