Exploratory Analysis of Functional Data via Clustering and Optimal Segmentation

We propose in this paper an exploratory analysis algorithm for functional data. The method partitions a set of functions into $K$ clusters and represents each cluster by a simple prototype (e.g., piecewise constant). The total number of segments in the prototypes, $P$, is chosen by the user and optimally distributed among the clusters via two dynamic programming algorithms. The practical relevance of the method is shown on two real world datasets

Consolidation, Scale Economies and Technological Change in Japanese Banking

The paper examines the technological structure of the Japanese banking sector before the onset of the banking crisis and structural reforms of the 90s in order to shade light on the logic of the recent trend to consolidation in the industry. While diseconomies of scale are shown to be pervasive in the large banks, defying the rationale for consolidation, the paper presents evidence of an underlying technological progress that operates to significantly increase the industry’s efficient minimum size, generating economies at larger banks, thus justifying the ongoing trend in consolidation. The results suggest that, to the extent that consumers can benefit from lower costs of bank production, policies that promote a more concentrated banking structure might be consistent with public interest.http://deepblue.lib.umich.edu/bitstream/2027.42/40133/3/wp747.pd

Consolidation, Scale Economics and Technological Change in Japanese Banking

The paper examines the technological structure of the Japanese banking sector before the onset of the banking crisis and structural reforms of the 90s in order to shade light on the logic of the recent trend to consolidation in the industry. While diseconomies of scale are shown to be pervasive in the large banks, defying the rationale for consolidation, the paper presents evidence of an underlying technological progress that operates to significantly increase the industry’s efficient minimum size, generating economies at larger banks, thus justifying the ongoing trend in consolidation. The results suggest that, to the extent that consumers can benefit from lower costs of bank production, policies that promote a more concentrated banking structure might be consistent with public interest.http://deepblue.lib.umich.edu/bitstream/2027.42/57258/1/wp878 .pd

Hashing for Similarity Search: A Survey

Similarity search (nearest neighbor search) is a problem of pursuing the data items whose distances to a query item are the smallest from a large database. Various methods have been developed to address this problem, and recently a lot of efforts have been devoted to approximate search. In this paper, we present a survey on one of the main solutions, hashing, which has been widely studied since the pioneering work locality sensitive hashing. We divide the hashing algorithms two main categories: locality sensitive hashing, which designs hash functions without exploring the data distribution and learning to hash, which learns hash functions according the data distribution, and review them from various aspects, including hash function design and distance measure and search scheme in the hash coding space

Sequential Design for Ranking Response Surfaces

We propose and analyze sequential design methods for the problem of ranking several response surfaces. Namely, given $L \ge 2$ response surfaces over a continuous input space $\cal X$, the aim is to efficiently find the index of the minimal response across the entire $\cal X$. The response surfaces are not known and have to be noisily sampled one-at-a-time. This setting is motivated by stochastic control applications and requires joint experimental design both in space and response-index dimensions. To generate sequential design heuristics we investigate stepwise uncertainty reduction approaches, as well as sampling based on posterior classification complexity. We also make connections between our continuous-input formulation and the discrete framework of pure regret in multi-armed bandits. To model the response surfaces we utilize kriging surrogates. Several numerical examples using both synthetic data and an epidemics control problem are provided to illustrate our approach and the efficacy of respective adaptive designs.Comment: 26 pages, 7 figures (updated several sections and figures