no code implementations • 21 Oct 2019 • Rianne de Heide, Alisa Kirichenko, Nishant Mehta, Peter Grünwald
We study generalized Bayesian inference under misspecification, i. e. when the model is 'wrong but useful'.
no code implementations • WS 2018 • Avery Hiebert, Cole Peterson, Alona Fyshe, Nishant Mehta
While Long Short-Term Memory networks (LSTMs) and other forms of recurrent neural network have been successfully applied to language modeling on a character level, the hidden state dynamics of these models can be difficult to interpret.
no code implementations • 24 Jun 2014 • Mark D. Reid, Rafael M. Frongillo, Robert C. Williamson, Nishant Mehta
Mixability is a property of a loss which characterizes when fast convergence is possible in the game of prediction with expert advice.
no code implementations • NeurIPS 2012 • Nishant Mehta, Dongryeol Lee, Alexander G. Gray
We show theoretically that minimax MTL tends to avoid worst case outcomes on newly drawn test tasks in the learning to learn (LTL) test setting.