
Generalization Properties of Stochastic Optimizers via Trajectory Analysis
Despite the ubiquitous use of stochastic optimization algorithms in mach...
read it

LocalNewton: Reducing Communication Bottleneck for Distributed Learning
To address the communication bottleneck problem in distributed optimizat...
read it

Boundary thickness and robustness in learning models
Robustness of machine learning models to various adversarial and nonadv...
read it

Bayesian Coresets: An Optimization Perspective
Bayesian coresets have emerged as a promising approach for implementing ...
read it

Improved guarantees and a multipledescent curve for the Column Subset Selection Problem and the Nyström method
The Column Subset Selection Problem (CSSP) and the Nyström method are am...
read it

Learning Sparse Distributions using Iterative Hard Thresholding
Iterative hard thresholding (IHT) is a projected gradient descent algori...
read it

On Linear Convergence of Weighted Kernel Herding
We provide a novel convergence analysis of two popular sampling algorith...
read it

Interpreting Black Box Predictions using Fisher Kernels
Research in both machine learning and psychology suggests that salient e...
read it

Boosting Black Box Variational Inference
Approximating a probability density in a tractable manner is a central t...
read it

IHT dies hard: Provable accelerated Iterative Hard Thresholding
We study both in theory and practice the use of momentum motions in ...
read it

Boosting Variational Inference: an Optimization Perspective
Variational Inference is a popular technique to approximate a possibly i...
read it

Scalable Greedy Feature Selection via Weak Submodularity
Greedy algorithms are widely used for problems in machine learning such ...
read it

On Approximation Guarantees for Greedy Low Rank Optimization
We provide new approximation guarantees for greedy low rank matrix estim...
read it

A Unified Optimization View on Generalized Matching Pursuit and FrankWolfe
Two of the most fundamental prototypes of greedy optimization are the ma...
read it

Information Projection and Approximate Inference for Structured Sparse Variables
Approximate inference via information projection has been recently intro...
read it

Pursuits in Structured NonConvex Matrix Factorizations
Efficiently representing real world data in a succinct and parsimonious ...
read it

Towards a Better Understanding of Predict and Count Models
In a recent paper, Levy and Goldberg pointed out an interesting connecti...
read it
Rajiv Khanna
is this you? claim profile