Well File:
- Well Planning ( results)
- Shallow Hazard Analysis ( results)
- Well Plat ( results)
- Wellbore Schematic ( results)
- Directional Survey ( results)
- Fluid Sample ( results)
- Log ( results)
- Density ( results)
- Gamma Ray ( results)
- Mud ( results)
- Resistivity ( results)
- Report ( results)
- Daily Report ( results)
- End of Well Report ( results)
- Well Completion Report ( results)
- Rock Sample ( results)
Kiran K. Thekumparampil
Robustness of conditional GANs to noisy labels
Kiran K. Thekumparampil, Ashish Khetan, Zinan Lin, Sewoong Oh
Neural Information Processing Systems http://nips.cc/
Efficient Algorithms for Smooth Minimax Optimization
Kiran K. Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
In terms of g(, y), we consider two settings - strongly convex and nonconvex - and improve upon the best known rates in both. For strongly-convex g(, y), y, we propose a new direct optimal algorithm combining Mirror-Prox and Nesterov's AGD, and show that it can find global optimum in Õ (1/k
Robustness of conditional GANs to noisy labels
Kiran K. Thekumparampil, Ashish Khetan, Zinan Lin, Sewoong Oh
Neural Information Processing Systems http://nips.cc/
Efficient Algorithms for Smooth Minimax Optimization
Kiran K. Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh
In terms of g(, y), we consider two settings - strongly convex and nonconvex - and improve upon the best known rates in both. For strongly-convex g(, y), y, we propose a new direct optimal algorithm combining Mirror-Prox and Nesterov's AGD, and show that it can find global optimum in Õ (1/k