Underestimate Sequences via Quadratic Averaging. - Chenxin Ma; Naga Venkata C. Gudapati; Majid Jahani; Rachael Tappenden; Martin Takác 001 (CoRR, 2017)

Quasi-Newton Methods for Deep Learning: Forget the Past, Just Sample. - Albert S. Berahas; Majid Jahani; Martin Takác 001 (CoRR, 2019)

Don't Forget Your Teacher: A Corrective Reinforcement Learning Framework. - MohammadReza Nazari; Majid Jahani; Lawrence V. Snyder; Martin Takác 001 (CoRR, 2019)

Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy. - Majid Jahani; Xi He 004; Chenxin Ma; Aryan Mokhtari; Dheevatsa Mudigere; Alejandro Ribeiro; Martin Takác 001 (AISTATS, 2020)

Scaling Up Quasi-newton Algorithms: Communication Efficient Distributed SR1. - Majid Jahani; MohammadReza Nazari; Sergey Rusakov 001; Albert S. Berahas; Martin Takác 001 (LOD (1), 2020)

DynNet: Physics-based neural architecture design for linear and nonlinear structural response modeling and prediction. - Soheil Sadeghi Eshkevari; Martin Takác 001; Shamim N. Pakzad; Majid Jahani (CoRR, 2020)

SONIA: A Symmetric Blockwise Truncated Optimization Algorithm. - Majid Jahani; MohammadReza Nazari; Rachael Tappenden; Albert S. Berahas; Martin Takác 001 (AISTATS, 2021)

Fast and safe: accelerated gradient methods with optimality certificates and underestimate sequences. - Majid Jahani; Naga Venkata C. Gudapati; Chenxin Ma; Rachael Tappenden; Martin Takác 001 (Comput. Optim. Appl., 2021)

Doubly Adaptive Scaled Algorithm for Machine Learning Using Second-Order Information. - Majid Jahani; Sergey Rusakov 001; Zheng Shi; Peter Richtárik; Michael W. Mahoney; Martin Takác 001 (ICLR, 2022)

Quasi-Newton methods for machine learning: forget the past, just sample. - Albert S. Berahas; Majid Jahani; Peter Richtárik; Martin Takác 001 (Optim. Methods Softw., 2022)