For our CS229 project, we studied the problem of reliable computerized emotion recognition in images of human faces. First, we performed a preliminary exploration using SVM classifiers, and then developed an approach based on Deep Belief Nets. Deep Belief Nets, or DBNs, are probabilistic generative models composed of multiple layers of stochastic latent variables, where each “building block” la...

using greedy clustering method to solve capacitated location-routing problem with fuzzy demands abstract in this paper, the capacitated location routing problem with fuzzy demands (clrp_fd) is considered. in clrp_fd, facility location problem (flp) and vehicle routing problem (vrp) are observed simultaneously. indeed the vehicles and the depots have a predefined capacity to serve the customerst...

We consider a setting for Inverse Reinforcement Learning (IRL) where the learner is extended with the ability to actively select multiple environments, observing an agent’s behavior on each environment. We first demonstrate that if the learner can experiment with any transition dynamic on some fixed set of states and actions, then there exists an algorithm that reconstructs the agent’s reward f...

As a model for nonlinear approximation from a redundant set of time-frequency atoms, we consider approximation in L 2 (IR) with linear combinations of Walsh at oms. Best approximation can be realized with a fast algorithm when the class of approximants is restricted to linear combinations of pairwise orthogonal atoms. We describe the eeect of this restriction on approximation rates, and then di...

7 We propose a novel, efficient approach for obtaining high-quality experimental designs for 8 event-related functional magnetic resonance imaging (ER-fMRI). Our approach combines a 9 greedy hillclimbing algorithm and a cyclic permutation method. When searching for optimal 10 ER-fMRI designs, the proposed approach focuses only on a promising restricted class of 11 designs with equal frequency o...

Abstract. We present a new analysis of the greedy algorithm for the problem of finding a minimum spanning subset in -polymatroids. This algorithm has a performance ratio of approximately , which is best possible for large . A consequence of this algorithm is a polynomial time approximation algorithm with approximation ratio for finding minimum weight spanning subhypergraphs in -restricted hyper...

Previous research in cross-document entity coreference has generally been restricted to the offline scenario where the set of documents is provided in advance. As a consequence, the dominant approach is based on greedy agglomerative clustering techniques that utilize pairwise vector comparisons and thus require O(n2) space and time. In this paper we explore identifying coreferent entity mention...

The classes Ar and Sr are de ned as the classes of those graphs, where the minimum degree greedy algorithm always approximates the maximum independent set (MIS) problem within a factor of r, respectively, where this algorithm has a sequence of choices that yield an output that is at most a factor r from optimal, r 1 a rational number. It is shown that deciding whether a given graph belongs to A...