Interactive Submodular Set Cover

We introduce a natural generalization of submodular set cover and exact active learning with a finite hypothesis class (query learning). We call this new problem interactive submodular set cover. Applications include advertising in social networks with hidden information. We give an approximation guarantee for a novel greedy algorithm and give a hardness of approximation result which matches up to constant factors. We also discuss negative results for simpler approaches and present encouraging early experimental results.Comment: 15 pages, 1 figur

Education Governors for the 21st Century

Provides guidance for state leaders on how they can promote education reform through strategic alliances with educators, business leaders, and communities. Includes examples of leaders who have taken different approaches to school improvement

Blue Crab, Callinectes sapidus, Retention Rates in Different Trap Meshes

Percent escapements of blue crabs, Callinectes sapidus, by size and sex were determined for commercially available 38.1 mm square and hexagonal meshes and for five experimental squares. Commercial trap mesh sizes retained excessive numbers of sublegal blue crabs. Based on the criteria of maximizing sublegal crab escapement without an unacceptable loss of legal blue crabs, the 44.4 mm square (as measured from the inside of adjacent corners) was optimum and superior to either trap mesh used by fishermen

An in vitro assay for neural crest cell migration through the somites

Neural crest cells in the trunk of the avian embryo come into contact with the somites and neural tube during the course of their migration. However, the relationship between the somites and the early migratory routes followed by these cells is not yet completely understood. Here, we use a tissue culture assay to examine if avian neural crest cells migrate through the somites. Cultures of quail somites were prepared from four adjacent regions along the neural axis in the trunk. Each region had four pairs of consecutive somites with region I being most anterior and region IV containing the last four segments. Within each region, the somites were separated from other tissues by enzymatic digestion and plated onto collagen-coated dishes. Immuno-cytochemical techniques were used to confirm that no neural crest cells, recognized by the HNK-1 antibody, were present on the surface of the somites at the time of explantation. After several days in culture, the explanted somites were screened to identify pigment cells. Because neural crest cells give rise to all of the melanocytes in the trunk, the presence of pigment cells indicated that neural crest precursors were contained within the initial explant. After 5–11 days in vitro, the percentage of somite cultures containing pigment cells in regions I through IV, respectively, was 36%, 51%, 31% and 1%. These results suggest that neural crest cells migrate through the somitic mesenchyme and first enter the somites between 5 to 9 segments rostral to the most recently formed somite

An Ensemble-based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy

Etsy is a global marketplace where people across the world connect to make, buy and sell unique goods. Sellers at Etsy can promote their product listings via advertising campaigns similar to traditional sponsored search ads. Click-Through Rate (CTR) prediction is an integral part of online search advertising systems where it is utilized as an input to auctions which determine the final ranking of promoted listings to a particular user for each query. In this paper, we provide a holistic view of Etsy's promoted listings' CTR prediction system and propose an ensemble learning approach which is based on historical or behavioral signals for older listings as well as content-based features for new listings. We obtain representations from texts and images by utilizing state-of-the-art deep learning techniques and employ multimodal learning to combine these different signals. We compare the system to non-trivial baselines on a large-scale real world dataset from Etsy, demonstrating the effectiveness of the model and strong correlations between offline experiments and online performance. The paper is also the first technical overview to this kind of product in e-commerce context

Active Semi-Supervised Learning Using Sampling Theory for Graph Signals

We consider the problem of offline, pool-based active semi-supervised learning on graphs. This problem is important when the labeled data is scarce and expensive whereas unlabeled data is easily available. The data points are represented by the vertices of an undirected graph with the similarity between them captured by the edge weights. Given a target number of nodes to label, the goal is to choose those nodes that are most informative and then predict the unknown labels. We propose a novel framework for this problem based on our recent results on sampling theory for graph signals. A graph signal is a real-valued function defined on each node of the graph. A notion of frequency for such signals can be defined using the spectrum of the graph Laplacian matrix. The sampling theory for graph signals aims to extend the traditional Nyquist-Shannon sampling theory by allowing us to identify the class of graph signals that can be reconstructed from their values on a subset of vertices. This approach allows us to define a criterion for active learning based on sampling set selection which aims at maximizing the frequency of the signals that can be reconstructed from their samples on the set. Experiments show the effectiveness of our method.Comment: 10 pages, 6 figures, To appear in KDD'1

Profiles in Exhaustion and Pomposity: the Everyday Life of Komsomol cadres in the 1920s

The article examines the daily lives of Young Communist League (Komsomol) cadres in the 1920s argue that their ability to establish local authority through consent was often undermined by their everyday conditions. The article treats the emergence of the Komsomol’s nomenklatura and cadre appointment system after the Russian civil war, cadre workload, working conditions, health, attitudes, and the Komsomol leadership’s efforts to subordinate cadre malfeasance and corruption through public scandal. The article demonstrates that without a sturdy material base upon which to generate consent, local Komsomol cadres often relied on domination to exert their authority over their rank and file members and to some extent the local population. This reliance ultimately perpetuated itself. The more cadres employed coercion, the more the means of consent atrophied, which led them to turn time and again to domination. The use of domination over consent had grave implications on the nature of Bolshevik rule. Often Komsomol cadres were the only representative of the Soviet state in rural localities, and their methods of garnering authority were representative of prevailing trends of Bolshevik governance throughout the 1920s.</jats:p