Shobha Venkataraman

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All published works

Action	Title	Year	Authors
+	Theseus: A Library for Differentiable Nonlinear Optimization	2022	Luis Villaseñor-Pineda Taosha Fan Maurizio Monge Shobha Venkataraman Paloma Sodhi Ricky Chen Joseph D. Ortiz Daniel DeTone Austin Wang Stuart Anderson
+	CrypTen: Secure Multi-Party Computation Meets Machine Learning	2021	Brian Knott Shobha Venkataraman Awni Hannun Shubhabrata Sengupta Mark Ibrahim Laurens van der Maaten
+	CrypTen: Secure Multi-Party Computation Meets Machine Learning	2021	Brian Knott Shobha Venkataraman Awni Hannun Shubho Sengupta Mark Ibrahim Laurens van der Maaten
+	Neural Fixed-Point Acceleration for Convex Optimization	2021	Shobha Venkataraman Brandon Amos
+	Neural Fixed-Point Acceleration for Convex Optimization	2021	Shobha Venkataraman Brandon Amos
+	CrypTen: Secure Multi-Party Computation Meets Machine Learning	2021	Brian Knott Shobha Venkataraman Awni Hannun Shubho Sengupta Mark Ibrahim Laurens van der Maaten
+	Neural Fixed-Point Acceleration for Convex Optimization	2021	Shobha Venkataraman Brandon Amos

Common Coauthors

Coauthor	Papers Together
Brandon Amos	4
Awni Hannun	3
Mark Ibrahim	3
Laurens van der Maaten	3
Brian Knott	3
Shubho Sengupta	2
Stuart Anderson	1
Austin Wang	1
Shubhabrata Sengupta	1
Joseph D. Ortiz	1
Ricky Chen	1
Paloma Sodhi	1
Jing Dong	1
Maurizio Monge	1
Daniel DeTone	1
Taosha Fan	1
Mustafa Mukadam	1
Luis Villaseñor-Pineda	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	The numerical treatment of a single nonlinear equation	1970	A. S. Householder	1
+	Anderson Acceleration for Fixed-Point Iterations	2011	Homer F. Walker Peng Ni	1
+ PDF Chat	A class of methods for solving nonlinear simultaneous equations	1965	C. G. Broyden	1
+	Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias	1965	Stanley L. Warner	1
+ PDF Chat	Iterative Procedures for Nonlinear Integral Equations	1965	Donald G. Anderson	1
+	Poisoning Attacks against Support Vector Machines	2012	Battista Biggio Blaine Nelson Pavel Laskov	1
+	Share Conversion, Pseudorandom Secret-Sharing and Applications to Secure Computation	2005	Ronald Cramer Ivan Damgård Yuval Ishai	1
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	1
+ PDF Chat	Robust principal component analysis?	2011	Emmanuel J. Candès Xiaodong Li Yi Ma John Wright	1
+ PDF Chat	The NumPy Array: A Structure for Efficient Numerical Computation	2011	Stéfan van der Walt Steven C. Colbert Gaël Varoquaux	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+ PDF Chat	Conic Optimization via Operator Splitting and Homogeneous Self-Dual Embedding	2016	Brendan O’Donoghue Eric Chu Neal Parikh Stephen Boyd	1
+	Learning to Optimize	2016	Ke Li Jitendra Malik	1
+ PDF Chat	Deep Learning with Differential Privacy	2016	Martı́n Abadi Andy Chu Ian Goodfellow H. Brendan McMahan Ilya Mironov Kunal Talwar Li Zhang	1
+	On Differentiating Parameterized Argmin and Argmax Problems with Application to Bi-level Optimization	2016	Stephen Jay Gould Basura Fernando Anoop Cherian Peter Anderson Rodrigo Santa Cruz Edison Guo	1
+	Wav2Letter: an End-to-End ConvNet-based Speech Recognition System	2016	Ronan Collobert Christian Puhrsch Gabriel Synnaeve	1
+	Neural Architecture Search with Reinforcement Learning	2016	Barret Zoph Quoc V. Le	1
+	Towards A Rigorous Science of Interpretable Machine Learning	2017	Finale Doshi‐Velez Been Kim	1
+	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	2017	Chelsea Finn Pieter Abbeel Sergey Levine	1
+	Gazelle: A Low Latency Framework for Secure Neural Network Inference	2018	Chiraag Juvekar Vinod Vaikuntanathan Anantha P. Chandrakasan	1
+	A generic framework for privacy preserving deep learning	2018	Théo Ryffel Andrew Trask Morten Dahl Bobby Wagner Jason Mancuso Daniel Rueckert Jonathan Passerat‐Palmbach	1
+	TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning	2019	Akshay Agrawal Akshay Naresh Modi Alexandre Passos Allen Lavoie Ashish Agarwal Asim Shankar Igor Ganichev Josh Levenberg Mingsheng Hong Rajat Monga	1
+	Using learned optimizers to make models robust to input noise	2019	Luke Metz Niru Maheswaranathan Jonathon Shlens Jascha Sohl‐Dickstein Ekin D. Cubuk	1
+	Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation	2014	Kyunghyun Cho Bart van Merriënboer Çaǧlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio	1
+	Learning Combinatorial Optimization Algorithms over Graphs	2017	Hanjun Dai Elias B. Khalil Yuyu Zhang Bistra Dilkina Le Song	1
+	Very Deep Convolutional Networks for Large-Scale Image Recognition	2014	Karen Simonyan Andrew Zisserman	1
+ PDF Chat	Meta-Learning With Differentiable Convex Optimization	2019	Kwonjoon Lee Subhransu Maji Avinash Ravichandran Stefano Soatto	1
+	A Semismooth Newton Method for Fast, Generic Convex Programming	2017	Alnur Ali Eric Wong J. Zico Kolter	1
+	Attention is All you Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	1
+	Differentiable MPC for End-to-end Planning and Control	2018	Brandon Amos Ivan Jimenez Jacob Sacks Byron Boots J. Zico Kolter	1
+	Learning to learn by gradient descent by gradient descent	2016	Marcin Andrychowicz Misha Denil Sergio Luis Suárez Gómez Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas	1
+	OptNet: differentiable optimization as a layer in neural networks	2017	Brandon Amos J. Zico Kolter	1
+	Learning Latent Permutations with Gumbel-Sinkhorn Networks	2018	Gonzalo E. Mena David Belanger Scott W. Linderman Jasper Snoek	1
+	Differentiable Convex Optimization Layers	2019	Akshay Agrawal Brandon Amos Shane Barratt Stephen Boyd Steven Diamond J. Zico Kolter	1
+	PyTorch: An Imperative Style, High-Performance Deep Learning Library	2019	Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga	1
+ PDF Chat	Solution refinement at regular points of conic problems	2019	Enzo Busseti Walaa M. Moursi S. T. P. Boyd	1
+	Deep Equilibrium Models	2019	Shaojie Bai J. Zico Kolter Vladlen Koltun	1
+	Secure multiparty computations in floating-point arithmetic	2020	Chuan Guo Awni Hannun Brian Knott Laurens van der Maaten Mark Tygert Ruiyu Zhu	1
+	Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning	2020	Harsh Chaudhari Rahul Rachuri Ajith Suresh	1
+ PDF Chat	CrypTFlow: Secure TensorFlow Inference	2020	Nishant Kumar Mayank Rathee Nishanth Chandran Divya Gupta Aseem Rastogi Rahul Sharma	1
+	Multiscale Deep Equilibrium Models	2020	Shaojie Bai Vladlen Koltun J. Zico Kolter	1
+	A Learning-boosted Quasi-Newton Method for AC Optimal Power Flow	2020	Kyri Baker	1
+	Hypersolvers: Toward Fast Continuous-Depth Models	2020	Michael Poli Stefano Massaroli Atsushi Yamashita Hajime Asama Jinkyoo Park	1
+ PDF Chat	Machine learning for combinatorial optimization: A methodological tour d’horizon	2020	Yoshua Bengio Andrea Lodi Antoine Prouvost	1
+	Fourier Neural Operator for Parametric Partial Differential Equations	2020	Zongyi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu Kaushik Bhattacharya Andrew M. Stuart Anima Anandkumar	1
+ PDF Chat	A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification	2020	Veneta Haralampieva Daniel Rueckert Jonathan Passerat‐Palmbach	1
+ PDF Chat	Globally Convergent Type-I Anderson Acceleration for Nonsmooth Fixed-Point Iterations	2020	Junzi Zhang Brendan O’Donoghue Stephen Boyd	1
+ PDF Chat	ASTRA	2019	Harsh Chaudhari Ashish Choudhury Arpita Patra Ajith Suresh	1
+	BLAZE: Blazing Fast Privacy-Preserving Machine Learning	2020	Arpita Patra Ajith Suresh	1
+ PDF Chat	Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning	2020	Sameer Wagh Shruti Tople Fabrice Benhamouda Eyal Kushilevitz Prateek Mittal Tal Rabin	1