Sashank J. Reddi
20 papers · 2010–2025 · 4 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π§ Keyword Pioneer π Renaissance Researcher (5) π Interdisciplinary Bridge π Conference Polyglot (4)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Renaissance Researcher
(5)
π€
Dynamic Duo
(12)
ποΈ
Keyword Collector
(50)
β
The Questioner
(2)
π
Conference Pioneer
π
Century Club
(20)
π
Trend Setter
Conferences
ICLR (7)
ICML (6)
NIPS (6)
AISTATS (1)
Top co-authors
Keywords
variance reduction
(5)
stochastic optimization
(4)
nonconvex optimization
(3)
stochastic gradient descent
(2)
language model
(2)
few-shot learning
(1)
natural language processing
(1)
efficient training
(1)
bayesian inference
(1)
transfer learning
(1)
finite-sum optimization
(1)
convergence analysis
(1)
model pretraining
(1)
neural network optimization
(1)
map estimation
(1)
parallel computing
(1)
posterior inference
(1)
lp relaxation
(1)
stochastic gradient
(1)
model compression
(1)
Papers
Structured Preconditioners in Adaptive Optimization: A Unified Analysis
ICML 2025
Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation
ICML 2025
Efficient stagewise pretraining via progressive subnetworks
ICLR 2025
Reasoning with Latent Thoughts: On the Power of Looped Transformers
ICLR 2025
Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
ICML 2024
Simplicity Bias via Global Convergence of Sharpness Minimization
ICML 2024
On the Inductive Bias of Stacking Towards Improving Reasoning
NIPS 2024
Differentially Private Adaptive Optimization with Delayed Preconditioners
ICLR 2023
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
ICLR 2023
Efficient Training of Language Models using Few-Shot Learning
ICML 2023
Adaptive Federated Optimization
ICLR 2021
Can gradient clipping mitigate label noise?
ICLR 2020
Stochastic Negative Mining for Learning with Large Output Spaces
AISTATS 2019
On the Convergence of Adam and Beyond
ICLR 2018
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds
NIPS 2016
Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization
NIPS 2016
Stochastic Variance Reduction for Nonconvex Optimization
ICML 2016
Variance Reduction in Stochastic Gradient Langevin Dynamics
NIPS 2016
On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants
NIPS 2015
MAP estimation in Binary MRFs via Bipartite Multi-cuts
NIPS 2010