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Parthe Pandit
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2020 – today
- 2024
- [c14]Amirhesam Abedsoltan, Parthe Pandit, Luis Rademacher, Mikhail Belkin:
On the Nyström Approximation for Preconditioning in Kernel Machines. AISTATS 2024: 3718-3726 - [i21]Neil Mallinar, Daniel Beaglehole, Libin Zhu, Adityanarayanan Radhakrishnan, Parthe Pandit, Mikhail Belkin:
Emergence in non-neural models: grokking modular arithmetic via average gradient outer product. CoRR abs/2407.20199 (2024) - [i20]Parthe Pandit, Zhichao Wang, Yizhe Zhu:
Universality of kernel random matrices and kernel regression in the quadratic regime. CoRR abs/2408.01062 (2024) - 2023
- [j4]Daniel Beaglehole, Mikhail Belkin, Parthe Pandit:
On the Inconsistency of Kernel Ridgeless Regression in Fixed Dimensions. SIAM J. Math. Data Sci. 5(4): 854-872 (2023) - [c13]Evan Becker, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher:
Local Convergence of Gradient Descent-Ascent for Training Generative Adversarial Networks. ACSSC 2023: 892-896 - [c12]Amirhesam Abedsoltan, Mikhail Belkin, Parthe Pandit:
Toward Large Kernel Models. ICML 2023: 61-78 - [i19]Amirhesam Abedsoltan, Mikhail Belkin, Parthe Pandit:
Toward Large Kernel Models. CoRR abs/2302.02605 (2023) - [i18]Evan Becker, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher:
Local Convergence of Gradient Descent-Ascent for Training Generative Adversarial Networks. CoRR abs/2305.08277 (2023) - [i17]Daniel Beaglehole, Adityanarayanan Radhakrishnan, Parthe Pandit, Mikhail Belkin:
Mechanism of feature learning in convolutional neural networks. CoRR abs/2309.00570 (2023) - [i16]Amirhesam Abedsoltan, Mikhail Belkin, Parthe Pandit, Luis Rademacher:
On the Nystrom Approximation for Preconditioning in Kernel Machines. CoRR abs/2312.03311 (2023) - 2022
- [c11]Evan Becker, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher:
Instability and Local Minima in GAN Training with Kernel Discriminators. NeurIPS 2022 - [c10]Neil Mallinar, James B. Simon, Amirhesam Abedsoltan, Parthe Pandit, Misha Belkin, Preetum Nakkiran:
Benign, Tempered, or Catastrophic: Toward a Refined Taxonomy of Overfitting. NeurIPS 2022 - [i15]Mojtaba Sahraee-Ardakan, Melikasadat Emami, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher:
Kernel Methods and Multi-layer Perceptrons Learn Linear Models in High Dimensions. CoRR abs/2201.08082 (2022) - [i14]Daniel Beaglehole, Mikhail Belkin, Parthe Pandit:
Kernel Ridgeless Regression is Inconsistent for Low Dimensions. CoRR abs/2205.13525 (2022) - [i13]Libin Zhu, Parthe Pandit, Mikhail Belkin:
A note on Linear Bottleneck networks and their Transition to Multilinearity. CoRR abs/2206.15058 (2022) - [i12]Neil Mallinar, James B. Simon, Amirhesam Abedsoltan, Parthe Pandit, Mikhail Belkin, Preetum Nakkiran:
Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting. CoRR abs/2207.06569 (2022) - [i11]Evan Becker, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher:
Instability and Local Minima in GAN Training with Kernel Discriminators. CoRR abs/2208.09938 (2022) - [i10]Adityanarayanan Radhakrishnan, Daniel Beaglehole, Parthe Pandit, Mikhail Belkin:
Feature learning in neural networks and kernel machines that recursively learn features. CoRR abs/2212.13881 (2022) - 2021
- [c9]Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher:
Implicit Bias of Linear RNNs. ICML 2021: 2982-2992 - [i9]Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher:
Implicit Bias of Linear RNNs. CoRR abs/2101.07833 (2021) - 2020
- [j3]Parthe Pandit
, Mojtaba Sahraee-Ardakan, Sundeep Rangan
Inference With Deep Generative Priors in High Dimensions. IEEE J. Sel. Areas Inf. Theory 1(1): 336-347 (2020) - [j2]Parthe Pandit
Generalized Autoregressive Linear Models for Discrete High-Dimensional Data. IEEE J. Sel. Areas Inf. Theory 1(3): 884-896 (2020) - [c8]Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher:
Generalization Error of Generalized Linear Models in High Dimensions. ICML 2020: 2892-2901 - [c7]Parthe Pandit, Mojtaba Sahraee-Ardakan, Sundeep Rangan, Philip Schniter, Alyson K. Fletcher:
Matrix Inference and Estimation in Multi-Layer Models. NeurIPS 2020 - [i8]Parthe Pandit, Mojtaba Sahraee-Ardakan, Sundeep Rangan, Philip Schniter, Alyson K. Fletcher:
Inference in Multi-Layer Networks with Matrix-Valued Unknowns. CoRR abs/2001.09396 (2020) - [i7]Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson K. Fletcher:
Generalization Error of Generalized Linear Models in High Dimensions. CoRR abs/2005.00180 (2020) - [i6]Melikasadat Emami, Mojtaba Sahraee-Ardakan, Parthe Pandit, Alyson K. Fletcher, Sundeep Rangan, Michael Trumpis, Brinnae Bent, Chia-Han Chiang, Jonathan Viventi:
Low-Rank Nonlinear Decoding of $μ$-ECoG from the Primary Auditory Cortex. CoRR abs/2005.05053 (2020)
2010 – 2019
- 2019
- [c6]Parthe Pandit, Mojtaba Sahraee-Ardakan, Arash A. Amini, Sundeep Rangan, Alyson K. Fletcher:
Sparse Multivariate Bernoulli Processes in High Dimensions. AISTATS 2019: 457-466 - [c5]Parthe Pandit, Mojtaba Sahraee, Sundeep Rangan, Alyson K. Fletcher:
Asymptotics of MAP Inference in Deep Networks. ISIT 2019: 842-846 - [i5]Parthe Pandit, Mojtaba Sahraee, Sundeep Rangan, Alyson K. Fletcher:
Asymptotics of MAP Inference in Deep Networks. CoRR abs/1903.01293 (2019) - [i4]Parthe Pandit, Mojtaba Sahraee-Ardakan, Arash A. Amini, Sundeep Rangan, Alyson K. Fletcher:
High-Dimensional Bernoulli Autoregressive Process with Long-Range Dependence. CoRR abs/1903.09631 (2019) - [i3]Parthe Pandit, Mojtaba Sahraee-Ardakan, Sundeep Rangan, Philip Schniter, Alyson K. Fletcher:
Inference with Deep Generative Priors in High Dimensions. CoRR abs/1911.03409 (2019) - 2018
- [j1]Parthe Pandit
A linear complementarity based characterization of the weighted independence number and the independent domination number in graphs. Discret. Appl. Math. 244: 155-169 (2018) - [c4]Parthe Pandit, Samuel Coogan
Discount-Based Pricing and Capacity Planning for EV Charging Under Stochastic Demand. ACC 2018: 6273-6278 - [c3]Alyson K. Fletcher, Parthe Pandit, Sundeep Rangan, Subrata Sarkar, Philip Schniter:
Plug-in Estimation in High-Dimensional Linear Inverse Problems: A Rigorous Analysis. NeurIPS 2018: 7451-7460 - 2017
- [c2]Parthe Pandit, Ankur A. Kulkarni:
Non-constructive lower bounds for binary asymmetric error correcting codes. NCC 2017: 1-6 - 2016
- [i2]Parthe Pandit, Ankur A. Kulkarni:
A linear complementarity based characterization of the weighted independence number and the independent domination number in graphs. CoRR abs/1603.05075 (2016) - [i1]Parthe Pandit, Ankur A. Kulkarni:
Refinement of the Equilibrium of Public Goods Games over Networks: Efficiency and Effort of Specialized Equilibria. CoRR abs/1607.02037 (2016) - 2015
- [c1]Prateek Verma, Vinutha T. P.
Structural segmentation of Hindustani concert audio with posterior features. ICASSP 2015: 136-140
Coauthor Index
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last updated on 2024-09-30 00:09 CEST by the dblp team
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