Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

no code implementations • 15 Oct 2022 • Anthony Zador, Sean Escola, Blake Richards, Bence Ölveczky, Yoshua Bengio, Kwabena Boahen, Matthew Botvinick, Dmitri Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad Koerding, Alexei Koulakov, Yann Lecun, Timothy Lillicrap, Adam Marblestone, Bruno Olshausen, Alexandre Pouget, Cristina Savin, Terrence Sejnowski, Eero Simoncelli, Sara Solla, David Sussillo, Andreas S. Tolias, Doris Tsao

Neuroscience has long been an essential driver of progress in artificial intelligence (AI).

Online Learning Without Prior Information

no code implementations • 7 Mar 2017 • Ashok Cutkosky, Kwabena Boahen

The vast majority of optimization and online learning algorithms today require some prior information about the data (often in the form of bounds on gradients or on the optimal parameter value).

Online Convex Optimization with Unconstrained Domains and Losses

no code implementations • NeurIPS 2016 • Ashok Cutkosky, Kwabena Boahen

We propose an online convex optimization algorithm (RescaledExp) that achieves optimal regret in the unconstrained setting without prior knowledge of any bounds on the loss functions.

Hyperparameter Optimization