Bamdev Mishra

According to our database1, Bamdev Mishra authored at least 48 papers between 2011 and 2020.

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Bibliography

2020
A Simple Approach to Learning Unsupervised Multilingual Embeddings.
CoRR, 2020

Learning Geometric Word Meta-Embeddings.
Proceedings of the 5th Workshop on Representation Learning for NLP, 2020

Geometry-aware domain adaptation for unsupervised alignment of word embeddings.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach.
Trans. Assoc. Comput. Linguistics, 2019

Riemannian Stochastic Variance Reduced Gradient Algorithm with Retraction and Vector Transport.
SIAM J. Optim., 2019

A Riemannian gossip approach to subspace learning on Grassmann manifold.
Mach. Learn., 2019

Riemannian optimization on the simplex of positive definite matrices.
CoRR, 2019

Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold.
CoRR, 2019

Adaptive stochastic gradient algorithms on Riemannian manifolds.
CoRR, 2019

Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Riemannian adaptive stochastic gradient algorithms on matrix manifolds.
Proceedings of the 36th International Conference on Machine Learning, 2019

Low-rank approximations of hyperbolic embeddings.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018
McTorch, a manifold optimization library for deep learning.
CoRR, 2018

Low-rank geometric mean metric learning.
CoRR, 2018

Bayesian Semi-Supervised Tensor Decomposition using Natural Gradients for Anomaly Detection.
CoRR, 2018

A Unified Framework for Domain Adaptation Using Metric Learning on Manifolds.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

A Dual Framework for Low-rank Tensor Completion.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Inexact trust-region algorithms on Riemannian manifolds.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Riemannian Stochastic Recursive Gradient Algorithm with Retraction and Vector Transport and Its Convergence Analysis.
Proceedings of the 35th International Conference on Machine Learning, 2018

A Unified Framework for Structured Low-rank Matrix Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifolds.
Proceedings of the 26th European Signal Processing Conference, 2018

Inductive Framework for Multi-Aspect Streaming Tensor Completion with Side Information.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Riemannian stochastic quasi-Newton algorithm with variance reduction and its convergence analysis.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Topological Interference Management With User Admission Control via Riemannian Optimization.
IEEE Trans. Wireless Communications, 2017

A two-dimensional decomposition approach for matrix completion through gossip.
CoRR, 2017

Riemannian stochastic variance reduced gradient.
CoRR, 2017

A Riemannian gossip approach to decentralized subspace learning on Grassmann manifold.
CoRR, 2017

A Saddle Point Approach to Structured Low-rank Matrix Learning in Large-scale Applications.
CoRR, 2017

A Sparse and Low-Rank Optimization Framework for Network Topology Control in Dense Fog-RAN.
Proceedings of the 85th IEEE Vehicular Technology Conference, 2017

2016
Riemannian Preconditioning.
SIAM J. Optim., 2016

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization.
IEEE Trans. Pattern Anal. Mach. Intell., 2016

Topological Interference Management with User Admission Control via Riemannian Optimization.
CoRR, 2016

A Sparse and Low-Rank Optimization Framework for Index Coding via Riemannian Optimization.
CoRR, 2016

A Riemannian gossip approach to decentralized matrix completion.
CoRR, 2016

Riemannian stochastic variance reduced gradient on Grassmann manifold.
CoRR, 2016

Low-rank tensor completion: a Riemannian manifold preconditioning approach.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Scaled stochastic gradient descent for low-rank matrix completion.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015
Riemannian preconditioning for tensor completion.
CoRR, 2015

Symmetry-invariant optimization in deep networks.
CoRR, 2015

Understanding symmetries in deep networks.
CoRR, 2015

Sparse plus low-rank autoregressive identification in neuroimaging time series.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2014
Manopt, a matlab toolbox for optimization on manifolds.
J. Mach. Learn. Res., 2014

Fixed-rank matrix factorizations and Riemannian low-rank optimization.
Comput. Stat., 2014

Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14).
CoRR, 2014

R3MC: A Riemannian three-factor algorithm for low-rank matrix completion.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

2013
Low-Rank Optimization with Trace Norm Penalty.
SIAM J. Optim., 2013

2012
A Riemannian geometry for low-rank matrix completion
CoRR, 2012

2011
Low-rank optimization for distance matrix completion.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011


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