2 citations · 7 across the 12 of their papers we have counts for
3 papers · 1 filter
Distributionally Robust K-Means Clustering
Vikrant Malik, Taylan Kargin, Babak Hassibi
K-means clustering is a workhorse of unsupervised learning, but it is notoriously brittle to outliers, distribution shifts, and limited sample sizes. Viewing k-means as Lloyd--Max…
Stochastic Mirror Descent in Average Ensemble Models
Taylan Kargin, Fariborz Salehi, Babak Hassibi
The stochastic mirror descent (SMD) algorithm is a general class of training algorithms, which includes the celebrated stochastic gradient descent (SGD), as a special case. It util…
Thompson Sampling Achieves Regret in Linear Quadratic Control
Taylan Kargin, Sahin Lale, Kamyar Azizzadenesheli +2
Thompson Sampling (TS) is an efficient method for decision-making under uncertainty, where an action is sampled from a carefully prescribed distribution which is updated based on t…