Papers:
(Distributed
Machine Learning)
Data-Dependent Convergence
For Distributed Stochastic Optimization
Avleen S. Bijral, Anand D. Sarwate and Nathan Srebro
(coming soon)
Mini-Batch Primal and Dual Methods
for SVMs (pdf)
Martin Takac, Avleen S. Bijral, Peter Richtarik and Nathan Srebro
In proceedings International Conference on Machine Learning (ICML) 2013.
On
Doubly Stochastic Graph Optimization
(pdf)
Avleen S Bijral and Nathan Srebro
In proceedings NIPS Workshop on Analyzing Networks and Learning with
Graphs 2009.
(Semi Supervised Learning and
Applications)
Semi-supervised
Learning with Density Based Distances
(pdf)
Avleen S Bijral, Nathan Ratliff and Nathan Srebro
In proceedings Uncertainty in Artificial Intelligence (UAI) 2011.
Traversable Path
Identification in Unstructured Terrains: A Markov Random Walk
Approach
(pdf)
Adam R Bates, Avleen S Bijral, Jane Mulligan and Greg Grudic
In proceedings IEEE Conference on Robotics and Automation (ICRA) 2009.
(Generative Models)
Mixture
of Watson Distributions: A Generative Model for Hyperspherical
Embeddings (pdf)
Avleen S Bijral, Markus Breitenbach and Greg Grudic
In proceedings Artificial Intelligence and Statistics (AISTATS) 2007.
Distributed
Mixture Density Estimation (pdf)
Avleen S Bijral
(Miscellaneous)
Expected
Lengths of k-shortest Paths in Lp-weighted Graphs (pdf)
Avleen
S Bijral
Graduate Coursework:
Discrete Mathematics, Stochastic Processes, Algorithms, Real and
Functional Analysis, Optimization,
Mathematical Statistics, Algebraic Statistics and Machine Learning