The analysis of online least squares estimation is at the heart of many stochastic sequential decision-making problems. We employ tools from the self-normalized processes to provi...
Non-negative spectrogram factorization algorithms such as probabilistic latent component analysis (PLCA) have been shown to be quite powerful for source separation. When training d...
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
We study the online ad-auctions problem introduced by Mehta et. al. [15]. We design a (1 − 1/e)competitive (optimal) algorithm for the problem, which is based on a clean primal-...
Power and performance benefits of scaling are lost to worst case margins as uncertainty of device characteristics is increasing. Adaptive techniques can dynamically adjust the mar...