Igor Molybog

According to our database, Igor Molybog authored at least 13 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Effective Long-Context Scaling of Foundation Models.

Wenhan Xiong, Jingyu Liu, Igor Molybog, Hejia Zhang, Prajjwal Bhargava, Rui Hou, Louis Martin, Rashi Rungta, Karthik Abinav Sankararaman, Barlas Oguz, Madian Khabsa, Han Fang, Yashar Mehdad, Sharan Narang, Kshitiz Malik, Angela Fan, Shruti Bhosale, Sergey Edunov, Mike Lewis, Sinong Wang, Hao Ma

CoRR, 2023

Llama 2: Open Foundation and Fine-Tuned Chat Models.

Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton-Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurélien Rodriguez, Robert Stojnic, Sergey Edunov, Thomas Scialom

CoRR, 2023

A Theory on Adam Instability in Large-Scale Machine Learning.

Igor Molybog, Peter Albert, Moya Chen, Zachary DeVito, David Esiobu, Naman Goyal, Punit Singh Koura, Sharan Narang, Andrew Poulton, Ruan Silva, Binh Tang, Diana Liskovich, Puxin Xu, Yuchen Zhang, Melanie Kambadur, Stephen Roller, Susan Zhang

CoRR, 2023

Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points.

Ziye Ma, Igor Molybog, Javad Lavaei, Somayeh Sojoudi

Proceedings of the International Conference on Machine Learning, 2023

2022

Role of sparsity and structure in the optimization landscape of non-convex matrix sensing.

Igor Molybog, Somayeh Sojoudi, Javad Lavaei

Math. Program., 2022

2021

When Does MAML Objective Have Benign Landscape?

Igor Molybog, Javad Lavaei

Proceedings of the IEEE Conference on Control Technology and Applications, 2021

No Spurious Solutions in Non-convex Matrix Sensing: Structure Compensates for Isometry.

Igor Molybog, Somayeh Sojoudi, Javad Lavaei

Proceedings of the 2021 American Control Conference, 2021

2020

Scalable and Robust State Estimation From Abundant But Untrusted Data.

Ming Jin, Igor Molybog, Reza Mohammadi-Ghazi, Javad Lavaei

IEEE Trans. Smart Grid, 2020

Conic Optimization for Quadratic Regression Under Sparse Noise.

Igor Molybog, Ramtin Madani, Javad Lavaei

J. Mach. Learn. Res., 2020

Global Convergence of MAML for LQR.

Igor Molybog, Javad Lavaei

CoRR, 2020

2019

Towards Robust and Scalable Power System State Estimation.

Ming Jin, Igor Molybog, Reza Mohammadi-Ghazi, Javad Lavaei

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

On Sampling Complexity of the Semidefinite Affine Rank Feasibility Problem.

Igor Molybog, Javad Lavaei

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Conic Optimization for Robust Quadratic Regression: Deterministic Bounds and Statistical Analysis.

Igor Molybog, Ramtin Madani, Javad Lavaei

Proceedings of the 57th IEEE Conference on Decision and Control, 2018