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Publication search results
found 181 matches
- 2024
- Vidush Singhal, Chaitanya Koparkar, Joseph Zullo, Artem Pelenitsyn, Michael Vollmer, Mike Rainey, Ryan Newton, Milind Kulkarni:
Optimizing Layout of Recursive Datatypes with Marmoset (Artifact). Dagstuhl Artifacts Ser. 10(2): 21:1-21:10 (2024) - Alexey F. Izmailov, Mikhail V. Solodov:
On Local Behavior of Newton-Type Methods Near Critical Solutions of Constrained Equations. J. Optim. Theory Appl. 203(2): 1103-1126 (2024) - Martin Brokate, Michael Ulbrich:
Corrigendum and Addendum: Newton Differentiability of Convex Functions in Normed Spaces and of a Class of Operators. SIAM J. Optim. 34(3): 3163-3166 (2024) - Andre Milzarek
, Fabian Schaipp
, Michael Ulbrich:
A Semismooth Newton Stochastic Proximal Point Algorithm with Variance Reduction. SIAM J. Optim. 34(1): 1157-1185 (2024) - Stefano van Gogh
, Subhadip Mukherjee
, Michal Rawlik, Alexandre Pereira, Simon Spindler, Marie-Christine Zdora
, Martin Stauber
, Zsuzsanna Varga, Marco Stampanoni:
Data-Driven Gradient Regularization for Quasi-Newton Optimization in Iterative Grating Interferometry CT Reconstruction. IEEE Trans. Medical Imaging 43(3): 1033-1044 (2024) - Tianyi Lin, Marco Cuturi, Michael I. Jordan:
A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport. AISTATS 2024: 145-153 - Vidush Singhal, Chaitanya Koparkar, Joseph Zullo, Artem Pelenitsyn, Michael Vollmer, Mike Rainey, Ryan Newton, Milind Kulkarni:
Optimizing Layout of Recursive Datatypes with Marmoset: Or, Algorithms {+} Data Layouts {=} Efficient Programs. ECOOP 2024: 38:1-38:28 - Chaitanya S. Koparkar
, Vidush Singhal
, Aditya Gupta
, Mike Rainey
, Michael Vollmer
, Artem Pelenitsyn
, Sam Tobin-Hochstadt
, Milind Kulkarni
, Ryan R. Newton
:
Garbage Collection for Mostly Serialized Heaps. ISMM 2024: 1-14 - Qurat ul ain Ali
, Dimitris S. Kolovos
, Antonio García-Domínguez
, Michael Bennett
, Joe Newton
, Piotr Zacharzewski
:
Advancing Domain-Specific High-Integrity Model-Based Tools: Insights and Future Pathways. MODELS 2024: 104-113 - Ruichen Jiang, Michal Derezinski, Aryan Mokhtari:
Stochastic Newton Proximal Extragradient Method. NeurIPS 2024 - Evan Hubinger, Carson Denison, Jesse Mu, Mike Lambert, Meg Tong, Monte MacDiarmid, Tamera Lanham, Daniel M. Ziegler, Tim Maxwell, Newton Cheng, Adam S. Jermyn, Amanda Askell, Ansh Radhakrishnan, Cem Anil, David Duvenaud, Deep Ganguli, Fazl Barez, Jack Clark, Kamal Ndousse, Kshitij Sachan, Michael Sellitto, Mrinank Sharma, Nova DasSarma, Roger Grosse, Shauna Kravec, Yuntao Bai, Zachary Witten, Marina Favaro, Jan Brauner, Holden Karnofsky, Paul F. Christiano, Samuel R. Bowman, Logan Graham, Jared Kaplan, Sören Mindermann, Ryan Greenblatt, Buck Shlegeris, Nicholas Schiefer, Ethan Perez:
Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training. CoRR abs/2401.05566 (2024) - Vidush Singhal, Chaitanya Koparkar, Joseph Zullo, Artem Pelenitsyn, Michael Vollmer, Mike Rainey, Ryan Newton, Milind Kulkarni:
Optimizing Layout of Recursive Datatypes with Marmoset. CoRR abs/2405.17590 (2024) - Ruichen Jiang, Michal Derezinski
, Aryan Mokhtari:
Stochastic Newton Proximal Extragradient Method. CoRR abs/2406.01478 (2024) - Amal Alphonse, Constantin Christof, Michael Hintermüller, Ioannis P. A. Papadopoulos:
A Globalized Inexact Semismooth Newton Method for Nonsmooth Fixed-point Equations involving Variational Inequalities. CoRR abs/2409.19637 (2024) - 2023
- Helmut Gfrerer
, Michael Mandlmayr, Jirí V. Outrata, Jan Valdman
:
On the SCD semismooth* Newton method for generalized equations with application to a class of static contact problems with Coulomb friction. Comput. Optim. Appl. 86(3): 1159-1191 (2023) - Martin Bencsik, Adam McVeigh
, Costas Tsakonas, Tarun Kumar
, Luke Chamberlain, Michael I. Newton
:
A Monitoring System for Carbon Dioxide in Honeybee Hives: An Indicator of Colony Health. Sensors 23(7): 3588 (2023) - Michael Arbel, Romain Menegaux, Pierre Wolinski:
Rethinking Gauss-Newton for learning over-parameterized models. NeurIPS 2023 - Hao Wang
, Michael Emmerich
, André H. Deutz
, Víctor Adrián Sosa-Hernández
, Oliver Schütze:
Experimental Results for the study "The Hypervolume Newton Method for Constrained Multi-Objective Optimization Problems". Zenodo, 2023 - Michael Arbel:
Rethinking Gauss-Newton for learning over-parameterized models. CoRR abs/2302.02904 (2023) - Tianyi Lin, Marco Cuturi, Michael I. Jordan:
A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport. CoRR abs/2310.14087 (2023) - 2022
- Omar Awile, Pramod S. Kumbhar, Nicolas Cornu, Salvador Dura-Bernal
, James Gonzalo King, Olli Lupton, Ioannis Magkanaris, Robert A. McDougal, Adam J. H. Newton, Fernando Pereira, Alexandru Savulescu
, Nicholas T. Carnevale, William W. Lytton, Michael L. Hines, Felix Schürmann:
Modernizing the NEURON Simulator for Sustainability, Portability, and Performance. Frontiers Neuroinformatics 16 (2022) - Martin Brokate, Michael Ulbrich
:
Newton Differentiability of Convex Functions in Normed Spaces and of a Class of Operators. SIAM J. Optim. 32(2): 1265-1287 (2022) - Hao-Jun Michael Shi, Yuchen Xie, Richard H. Byrd, Jorge Nocedal:
A Noise-Tolerant Quasi-Newton Algorithm for Unconstrained Optimization. SIAM J. Optim. 32(1): 29-55 (2022) - Benjamin Newton, Michael P. Scoggin, Anand Ganti, Uzoma Onunkwo, Vincent Hietala:
Clipping for Faster Wireless Network Simulation in ns-3. WNS3 2022: 65-72 - Helmut Gfrerer, Michael Mandlmayr, Jirí V. Outrata, Jan Valdman:
On the SCD semismooth* Newton method for generalized equations with application to a class of static contact problems with Coulomb friction. CoRR abs/2205.15129 (2022) - 2021
- Ioannis K. Argyros, Stepan Shakhno
, Roman Iakymchuk, Halyna Yarmola
, Michael I. Argyros:
Gauss-Newton-Secant Method for Solving Nonlinear Least Squares Problems under Generalized Lipschitz Conditions. Axioms 10(3): 158 (2021) - Zihao Zheng
, Aisha M. Mergaert, Irene M. Ong
, Miriam A. Shelef, Michael A. Newton
:
MixTwice: large-scale hypothesis testing for peptide arrays by variance mixing. Bioinform. 37(17): 2637-2643 (2021) - Ioannis K. Argyros
, Michael I. Argyros, Johan Ceballos, Mariana Ceballos, Daniel González
:
Extensions on a local convergence result by Dennis and Schnabel for Newton's method with applications. Comput. Math. Methods 3(5) (2021) - Andreas Fischer
, Alexey F. Izmailov
, Mikhail V. Solodov:
Accelerating convergence of the globalized Newton method to critical solutions of nonlinear equations. Comput. Optim. Appl. 78(1): 273-286 (2021) - Andreas Fischer
, Alexey F. Izmailov, Mikhail V. Solodov:
Unit stepsize for the Newton method close to critical solutions. Math. Program. 187(1): 697-721 (2021)
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