We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
We model the spatio-temporal variations of the shape of objects in a video sequence using a unique SVD-like decomposition. The decomposition is used to compute shape features, whi...
—In this paper, a robust stabilization of the uncertain singularly perturbed system via a networked state feedback with the transmission time-delay is addressed. Taking its nomin...
Zhiming Wang, Wei Liu, Haohui Dai, D. Subbaram Nai...
We study the performance of approximate Nash equilibria for congestion games with polynomial latency functions. We consider how much the price of anarchy worsens and how much the ...
George Christodoulou, Elias Koutsoupias, Paul G. S...
A constrained approximate dynamic programming (ADP) approach is presented for designing adaptive neural network (NN) controllers with closed-loop stability and performance guarante...