Nishanth Dikkala

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 39

Top Topics

Statistical Estimation

Multiple Images

Top Venues

Publications

Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka
Learning Neural Networks with Sparse Activations. COLT (2024)
Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath, Raghu Meka
Learning Neural Networks with Sparse Activations. CoRR (2024)
Mehran Kazemi, Nishanth Dikkala, Ankit Anand, Petar Devic, Ishita Dasgupta, Fangyu Liu, Bahare Fatemi, Pranjal Awasthi, Dee Guo, Sreenivas Gollapudi, Ahmed Qureshi
ReMI: A Dataset for Reasoning with Multiple Images. CoRR (2024)
Cenk Baykal, Dylan J. Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang
The Power of External Memory in Increasing Predictive Model Capacity. CoRR (2023)
Cenk Baykal, Dylan J. Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang
Alternating Updates for Efficient Transformers. NeurIPS (2023)
Cenk Baykal, Dylan Cutler, Nishanth Dikkala, Nikhil Ghosh, Rina Panigrahy, Xin Wang
Alternating Updates for Efficient Transformers. CoRR (2023)
Nishanth Dikkala, Nikhil Ghosh, Raghu Meka, Rina Panigrahy, Nikhil Vyas, Xin Wang
On the Benefits of Learning to Route in Mixture-of-Experts Models. EMNLP (2023)
Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang
A Theoretical View on Sparsely Activated Networks. NeurIPS (2022)
Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath
Do More Negative Samples Necessarily Hurt In Contrastive Learning? ICML (2022)
Nishanth Dikkala, Sankeerth Rao Karingula, Raghu Meka, Jelani Nelson, Rina Panigrahy, Xin Wang
Sketching based Representations for Robust Image Classification with Provable Guarantees. NeurIPS (2022)
Cenk Baykal, Nishanth Dikkala, Rina Panigrahy, Cyrus Rashtchian, Xin Wang
A Theoretical View on Sparsely Activated Networks. CoRR (2022)
Pranjal Awasthi, Nishanth Dikkala, Pritish Kamath
Do More Negative Samples Necessarily Hurt in Contrastive Learning? CoRR (2022)
Anthimos Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis
Statistical Estimation from Dependent Data. ICML (2021)
Nishanth Dikkala, Gal Kaplun, Rina Panigrahy
For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash Functions. CoRR (2021)
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Anthimos Vardis Kandiros
Learning Ising models from one or multiple samples. STOC (2021)
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Surbhi Goel, Anthimos Vardis Kandiros
Statistical Estimation from Dependent Data. CoRR (2021)
Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis
Minimax Estimation of Conditional Moment Models. CoRR (2020)
Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas
Logistic-Regression with peer-group effects via inference in higher order Ising models. CoRR (2020)
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Anthimos Vardis Kandiros
Estimating Ising Models from One Sample. CoRR (2020)
Nishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis
Minimax Estimation of Conditional Moment Models. NeurIPS (2020)
Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas
Logistic regression with peer-group effects via inference in higher-order Ising models. AISTATS (2020)
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti
Learning from weakly dependent data under Dobrushin's condition. CoRR (2019)
Ran Canetti, Aloni Cohen, Nishanth Dikkala, Govind Ramnarayan, Sarah Scheffler, Adam D. Smith
From Soft Classifiers to Hard Decisions: How fair can we be? FAT (2019)
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti
Learning from Weakly Dependent Data under Dobrushin's Condition. COLT (2019)
Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas
Regression from dependent observations. STOC (2019)
Constantinos Daskalakis, Nishanth Dikkala, Ioannis Panageas
Regression from Dependent Observations. CoRR (2019)
Constantinos Daskalakis, Nishanth Dikkala, Gautam Kamath
Testing Ising Models. IEEE Trans. Inf. Theory 65 (11) (2019)
Constantinos Daskalakis, Nishanth Dikkala, Nick Gravin
Testing Symmetric Markov Chains From a Single Trajectory. COLT (2018)
Constantinos Daskalakis, Nishanth Dikkala, Gautam Kamath
Testing Ising Models. SODA (2018)
Ran Canetti, Aloni Cohen, Nishanth Dikkala, Govind Ramnarayan, Sarah Scheffler, Adam D. Smith
From Soft Classifiers to Hard Decisions: How fair can we be? CoRR (2018)
Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti
HOGWILD!-Gibbs can be PanAccurate. NeurIPS (2018)
Constantinos Daskalakis, Nishanth Dikkala, Siddhartha Jayanti
HOGWILD!-Gibbs can be PanAccurate. CoRR (2018)
Constantinos Daskalakis, Nishanth Dikkala, Gautam Kamath
Concentration of Multilinear Functions of the Ising Model with Applications to Network Data. NIPS (2017)
Constantinos Daskalakis, Nishanth Dikkala, Gautam Kamath
Concentration of Multilinear Functions of the Ising Model with Applications to Network Data. CoRR (2017)
Constantinos Daskalakis, Nishanth Dikkala, Nick Gravin
Testing from One Sample: Is the casino really using a riffle shuffle? CoRR (2017)
Constantinos Daskalakis, Nishanth Dikkala, Gautam Kamath
Testing Ising Models. Electron. Colloquium Comput. Complex. 24 (2017)
Arturs Backurs, Nishanth Dikkala, Christos Tzamos
Tight Hardness Results for Maximum Weight Rectangles. CoRR (2016)
Constantinos Daskalakis, Nishanth Dikkala, Gautam Kamath
Testing Ising Models. CoRR (2016)
Arturs Backurs, Nishanth Dikkala, Christos Tzamos
Tight Hardness Results for Maximum Weight Rectangles. ICALP (2016)
Hedyeh Beyhaghi, Nishanth Dikkala, Éva Tardos
Brief Announcement: Effect of Strategic Grading and Early Offers in Matching Markets. SAGT (2015)
Hedyeh Beyhaghi, Nishanth Dikkala, Éva Tardos
Effect of Strategic Grading and Early Offers in Matching Markets. CoRR (2015)
Nishanth Dikkala, Éva Tardos
Can Credit Increase Revenue? WINE (2013)