101 citations · 105 across the 5 of their papers we have counts for
4 papers · 1 filter
Bet on Features: Anytime-Valid and Feature-Aware Auditing of Conditional Quantile Forecasters
Ivane Antonov, Sohom Mukherjee, Richard Pibernik +1
Black-box conditional quantile forecasts are widely used for sequential decisions under asymmetric costs. Once deployed, such forecasters must be monitored continuously as data str…
In-Context Learning for Data-Driven Censored Inventory Control
Sohom Mukherjee, Anh-Duy Pham, Richard Pibernik +1
We study inventory control with decision-dependent censoring, focusing on the censored or repeated newsvendor (R-NV), where each order quantity determines whether demand is fully o…
Locally Adaptive Federated Learning
Sohom Mukherjee, Nicolas Loizou, Sebastian U. Stich
Federated learning is a paradigm of distributed machine learning in which multiple clients coordinate with a central server to learn a model, without sharing their own training dat…
Why Random Pruning Is All We Need to Start Sparse
Advait Gadhikar, Sohom Mukherjee, Rebekka Burkholz
Random masks define surprisingly effective sparse neural network models, as has been shown empirically. The resulting sparse networks can often compete with dense architectures and…