Nishanth Dikkala
17 papers · 2017–2025 · 7 venues · across top CS/AI venues
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Research topics
Machine Learning
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Core Methods
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Optimization & Theory · Machine Learning
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Deep Learning
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Artificial Intelligence
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Core AI
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Optimization & Theory · Deep Learning
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Mathematics & Optimization
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Keywords
large language model
(3)
mixture of expert
(2)
sparse activation
(2)
representation learning
(2)
reasoning evaluation
(2)
ising model
(2)
dependent data
(2)
reasoning benchmark
(2)
logistic regression
(2)
statistical learning theory
(2)
polynomial function
(2)
transformer model
(2)
neural network optimization
(2)
multimodal learning
(1)
chain-of-thought reasoning
(1)
contrastive learning
(1)
sparse logistic regression
(1)
parameter estimation
(1)
image classification
(1)
network modeling
(1)
Papers
BIG-Bench Extra Hard
ACL 2025
Reasoning with Latent Thoughts: On the Power of Looped Transformers
ICLR 2025
Causal language modeling can elicit search and reasoning capabilities on logic puzzles
NeurIPS 2024
Learning Neural Networks with Sparse Activations
COLT 2024
ReMI: A Dataset for Reasoning with Multiple Images
NeurIPS 2024
Alternating Updates for Efficient Transformers
NeurIPS 2023
On the Benefits of Learning to Route in Mixture-of-Experts Models
EMNLP 2023
A Theoretical View on Sparsely Activated Networks
NeurIPS 2022
Do More Negative Samples Necessarily Hurt In Contrastive Learning?
ICML 2022
Sketching based Representations for Robust Image Classification with Provable Guarantees
NeurIPS 2022
Statistical Estimation from Dependent Data
ICML 2021
Logistic regression with peer-group effects via inference in higher-order Ising models
AISTATS 2020
Minimax Estimation of Conditional Moment Models
NeurIPS 2020
Learning from Weakly Dependent Data under Dobrushin’s Condition
COLT 2019
HOGWILD!-Gibbs can be PanAccurate
NeurIPS 2018
Testing Symmetric Markov Chains From a Single Trajectory
COLT 2018
Concentration of Multilinear Functions of the Ising Model with Applications to Network Data
NeurIPS 2017