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export results for "Natesh S. Pillai"
@inproceedings{DBLP:conf/nips/LiuG0P23, author = {Tianle Liu and Promit Ghosal and Krishnakumar Balasubramanian and Natesh S. Pillai}, title = {Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent}, booktitle = {NeurIPS}, year = {2023} }
@article{DBLP:journals/corr/abs-2305-14076, author = {Tianle Liu and Promit Ghosal and Krishnakumar Balasubramanian and Natesh S. Pillai}, title = {Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent}, journal = {CoRR}, volume = {abs/2305.14076}, year = {2023} }
@article{DBLP:journals/sac/DavisMSP22, author = {Andrew D. Davis and Youssef M. Marzouk and Aaron Smith and Natesh S. Pillai}, title = {Rate-optimal refinement strategies for local approximation {MCMC}}, journal = {Stat. Comput.}, volume = {32}, number = {4}, pages = {60}, year = {2022} }
@inproceedings{DBLP:conf/aistats/HoFGMP22, author = {Nhat Ho and Avi Feller and Evan Greif and Luke Miratrix and Natesh S. Pillai}, title = {Weak Separation in Mixture Models and Implications for Principal Stratification}, booktitle = {{AISTATS}}, series = {Proceedings of Machine Learning Research}, volume = {151}, pages = {5416--5458}, publisher = {{PMLR}}, year = {2022} }
@article{DBLP:journals/jap/MangoubiPS21, author = {Oren Mangoubi and Natesh S. Pillai and Aaron Smith}, title = {Simple conditions for metastability of continuous Markov chains}, journal = {J. Appl. Probab.}, volume = {58}, number = {1}, pages = {83--105}, year = {2021} }
@article{DBLP:journals/corr/abs-2003-10069, author = {Vishesh Jain and Natesh S. Pillai and Aaron Smith}, title = {Kac meets Johnson and Lindenstrauss: a memory-optimal, fast Johnson-Lindenstrauss transform}, journal = {CoRR}, volume = {abs/2003.10069}, year = {2020} }
@article{DBLP:journals/juq/ConradDMPS18, author = {Patrick R. Conrad and Andrew D. Davis and Youssef M. Marzouk and Natesh S. Pillai and Aaron Smith}, title = {Parallel Local Approximation {MCMC} for Expensive Models}, journal = {{SIAM/ASA} J. Uncertain. Quantification}, volume = {6}, number = {1}, pages = {339--373}, year = {2018} }
@article{DBLP:journals/corr/abs-1808-03230, author = {Oren Mangoubi and Natesh S. Pillai and Aaron Smith}, title = {Does Hamiltonian Monte Carlo mix faster than a random walk on multimodal densities?}, journal = {CoRR}, volume = {abs/1808.03230}, year = {2018} }
@article{DBLP:journals/sac/BornnPSW17, author = {Luke Bornn and Natesh S. Pillai and Aaron Smith and Dawn Woodard}, title = {The use of a single pseudo-sample in approximate Bayesian computation}, journal = {Stat. Comput.}, volume = {27}, number = {3}, pages = {583--590}, year = {2017} }
@inproceedings{DBLP:conf/aistats/BasseSP16, author = {Guillaume W. Basse and Aaron Smith and Natesh S. Pillai}, title = {Parallel Markov Chain Monte Carlo via Spectral Clustering}, booktitle = {{AISTATS}}, series = {{JMLR} Workshop and Conference Proceedings}, volume = {51}, pages = {1318--1327}, publisher = {JMLR.org}, year = {2016} }
@article{DBLP:journals/corr/JohndrowSPD16, author = {James E. Johndrow and Aaron Smith and Natesh S. Pillai and David B. Dunson}, title = {Inefficiency of Data Augmentation for Large Sample Imbalanced Data}, journal = {CoRR}, volume = {abs/1605.05798}, year = {2016} }
@article{DBLP:journals/jmlr/PillaiWLMW07, author = {Natesh S. Pillai and Qiang Wu and Feng Liang and Sayan Mukherjee and Robert L. Wolpert}, title = {Characterizing the Function Space for Bayesian Kernel Models}, journal = {J. Mach. Learn. Res.}, volume = {8}, pages = {1769--1797}, year = {2007} }
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