MIHash: Online Hashing with Mutual Information

Learning-based hashing methods are widely used for nearest neighbor retrieval, and recently, online hashing methods have demonstrated good performance-complexity trade-offs by learning hash functions from streaming data. In this paper, we first address a key challenge for online hashing: the binary codes for indexed data must be recomputed to keep pace with updates to the hash functions. We propose an efficient quality measure for hash functions, based on an information-theoretic quantity, mutual information, and use it successfully as a criterion to eliminate unnecessary hash table updates. Next, we also show how to optimize the mutual information objective using stochastic gradient descent. We thus develop a novel hashing method, MIHash, that can be used in both online and batch settings. Experiments on image retrieval benchmarks (including a 2.5M image dataset) confirm the effectiveness of our formulation, both in reducing hash table recomputations and in learning high-quality hash functions.Comment: International Conference on Computer Vision (ICCV), 201

Hashing as Tie-Aware Learning to Rank

Hashing, or learning binary embeddings of data, is frequently used in nearest neighbor retrieval. In this paper, we develop learning to rank formulations for hashing, aimed at directly optimizing ranking-based evaluation metrics such as Average Precision (AP) and Normalized Discounted Cumulative Gain (NDCG). We first observe that the integer-valued Hamming distance often leads to tied rankings, and propose to use tie-aware versions of AP and NDCG to evaluate hashing for retrieval. Then, to optimize tie-aware ranking metrics, we derive their continuous relaxations, and perform gradient-based optimization with deep neural networks. Our results establish the new state-of-the-art for image retrieval by Hamming ranking in common benchmarks.Comment: 15 pages, 3 figures. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 201

Exploring the Atmosphere of Neoproterozoic Earth: The Effect of O2_{2} on Haze Formation and Composition

Previous studies of haze formation in the atmosphere of the Early Earth have focused on N$_{2}$/CO$_{2}$/CH$_{4}$ atmospheres. Here, we experimentally investigate the effect of O$_{2}$ on the formation and composition of aerosols to improve our understanding of haze formation on the Neoproterozoic Earth. We obtained in situ size, particle density, and composition measurements of aerosol particles produced from N$_{2}$/CO$_{2}$/CH$_{4}$/O$_{2}$ gas mixtures subjected to FUV radiation (115-400 nm) for a range of initial CO$_{2}$/CH$_{4}$/O$_{2}$ mixing ratios (O$_{2}$ ranging from 2 ppm to 0.2\%). At the lowest O$_{2}$ concentration (2 ppm), the addition increased particle production for all but one gas mixture. At higher oxygen concentrations (20 ppm and greater) particles are still produced, but the addition of O$_{2}$ decreases the production rate. Both the particle size and number density decrease with increasing O$_{2}$, indicating that O$_{2}$ affects particle nucleation and growth. The particle density increases with increasing O$_{2}$. The addition of CO$_{2}$ and O$_{2}$ not only increases the amount of oxygen in the aerosol, but it also increases the degree of nitrogen incorporation. In particular, the addition of O$_{2}$ results in the formation of nitrate bearing molecules. The fact that the presence of oxygen bearing molecules increases the efficiency of nitrogen fixation has implications for the role of haze as a source of molecules required for the origin and evolution of life. The composition changes also likely affect the absorption and scattering behavior of these particles but optical properties measurements are required to fully understand the implications for the effect on the planetary radiative energy balance and climate.Comment: 15 pages, 3 tables, 8 figures, accepted in Astrophysical Journa

Effects of Community Exercise Therapy on Metabolic, Brain, Physical, and Cognitive Function Following Stroke : A Randomized Controlled Pilot Trial

© The Author(s) 2014.Peer reviewedPostprintPostprin

Change in Nutritional Status Modulates the Abundance of Critical Pre-initiation Intermediate Complexes During Translation Initiation \u3cem\u3ein Vivo\u3c/em\u3e

In eukaryotic translation initiation, eIF2∙GTP–Met-tRNAiMet ternary complex (TC) interacts with eIF3–eIF1–eIF5 complex to form the multifactor complex (MFC), while eIF2∙GDP associates with eIF2B for guanine nucleotide exchange. Gcn2p phosphorylates eIF2 to inhibit eIF2B. Here we evaluate the abundance of eIFs and their pre-initiation intermediate complexes in gcn2 deletion mutant grown under different conditions. We show that ribosomes are three times as abundant as eIF1, eIF2 and eIF5, while eIF3 is half as abundant as the latter three and hence, the limiting component in MFC formation. By quantitative immunoprecipitation, we estimate that ∼ 15% of the cellular eIF2 is found in TC during rapid growth in a complex rich medium. Most of the TC is found in MFC, and important, ∼ 40% of the total eIF2 is associated with eIF5 but lacks tRNAiMet. When the gcn2Δ mutant grows less rapidly in a defined complete medium, TC abundance increases threefold without altering the abundance of each individual factor. Interestingly, the TC increase is suppressed by eIF5 overexpression and Gcn2p expression. Thus, eIF2B-catalyzed TC formation appears to be fine-tuned by eIF2 phosphorylation and the novel eIF2/eIF5 complex lacking tRNAiMet

User Interface Engineering (KSU)

This Grants Collection for User Interface Engineering was created under a Round Twelve ALG Textbook Transformation Grant. Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process. Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials: Linked Syllabus Initial Proposal Final Reporthttps://oer.galileo.usg.edu/compsci-collections/1035/thumbnail.jp