We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
1 In this paper, we propose a hybrid approach for estimating the switching activities of the internal nodes in logic circuits. The new approach combines the advantages of the simul...
David Ihsin Cheng, Kwang-Ting Cheng, Deborah C. Wa...
We extract on the computer a number of moduli of uniform continuity for the first few elements of a sequence of closed terms t of G¨odel’s T of type (N→N)→(N→N). The gen...
Within the field of action recognition, features and descriptors are often engineered to be sparse and invariant to transformation. While sparsity makes the problem tractable, it ...
This paper addresses the problem of learning object models from egocentric video of household activities, using extremely weak supervision. For each activity sequence, we know onl...