Sushant Sachdeva
11 papers · 2012–2025 · 4 venues · across top CS/AI venues
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Research topics
Machine Learning
(10)
Optimization & Theory Β· Machine Learning
(8)
Mathematics & Optimization
(7)
Core Methods
(6)
Optimization
(6)
Mathematics
(4)
Deep Learning
(3)
Optimization & Theory Β· Deep Learning
(3)
Learning Types
(2)
Artificial Intelligence
(1)
Architectures
(1)
Bayesian & Probabilistic
(1)
Keywords
convex optimization
(3)
neural network optimization
(2)
semi-supervised learning
(2)
convergence analysis
(2)
gradient descent
(2)
link prediction
(1)
stochastic gradient descent
(1)
matrix decomposition
(1)
game theory
(1)
continuous optimization
(1)
independent component analysis
(1)
principal component analysis
(1)
matrix factorization
(1)
logistic regression
(1)
sparse recovery
(1)
sample complexity
(1)
graph laplacian
(1)
graph theory
(1)
representation learning
(1)
differential privacy
(1)
Papers
PREM: Privately Answering Statistical Queries with Relative Error
COLT 2025
A Convergent and Dimension-Independent Min-Max Optimization Algorithm
ICML 2022
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization
NeurIPS 2021
Faster Graph Embeddings via Coarsening
ICML 2020
Regularized linear autoencoders recover the principal components, eventually
NeurIPS 2020
Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression
NeurIPS 2019
Improved Semi-Supervised Learning with Multiple Graphs
AISTATS 2019
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model
NeurIPS 2019
Algorithms for Lipschitz Learning on Graphs
COLT 2015
Fast, Provable Algorithms for Isotonic Regression in all L_p-norms
NeurIPS 2015
Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders
NeurIPS 2012