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We present an integrated framework for using Convolutional Networks for classification , localization and detection. We show how a multiscale and sliding window approach can be efficiently implemented within a ConvNet. We also introduce a novel deep learning approach to localization by learning to predict object boundaries. Bounding boxes are then(More)
This article offers an empirical exploration on the use of character-level convolu-tional networks (ConvNets) for text classification. We constructed several large-scale datasets to show that character-level convolutional networks could achieve state-of-the-art or competitive results. Comparisons are offered against traditional models such as bag of words,(More)
" Physics of Optoelectronic and This dissertation explores the fundamental interactions between light and matter towards devices applications in the field of Opto-electronics and metal-optics, or plasmonics. In its core, this dissertation attempts, and succeeds to demonstrate strong enhancements of such interactions. Here, surface plasmon polaritons,(More)
Multi-view graph clustering aims to enhance clustering performance by integrating heterogeneous information collected in different domains. Each domain provides a different view of the data instances. Leveraging cross-domain information has been demonstrated an effective way to achieve better clustering results. Despite the previous success, existing(More)
How organ-specific metastatic traits arise in primary tumors remains unknown. Here, we show a role of the breast tumor stroma in selecting cancer cells that are primed for metastasis in bone. Cancer-associated fibroblasts (CAFs) in triple-negative (TN) breast tumors skew heterogeneous cancer cell populations toward a predominance of clones that thrive on(More)
Integrated optical modulators with high modulation speed, small footprint and large optical bandwidth are poised to be the enabling devices for on-chip optical interconnects. Semiconductor modulators have therefore been heavily researched over the past few years. However, the device footprint of silicon-based modulators is of the order of millimetres, owing(More)
As a promising tool for identifying genetic markers underlying phenotypic differences, genome-wide association study (GWAS) has been extensively investigated in recent years. In GWAS, detecting epistasis (or gene-gene interaction) is preferable over single locus study since many diseases are known to be complex traits. A brute force search is infeasible for(More)
Cells released from primary tumors seed metastases to specific organs by a nonrandom process, implying the involvement of biologically selective mechanisms. Based on clinical, functional, and molecular evidence, we show that the cytokine TGFbeta in the breast tumor microenvironment primes cancer cells for metastasis to the lungs. Central to this process is(More)
Recent theory has predicted a superlens that is capable of producing sub-diffraction-limited images. This superlens would allow the recovery of evanescent waves in an image via the excitation of surface plasmons. Using silver as a natural optical superlens, we demonstrated sub-diffraction-limited imaging with 60-nanometer half-pitch resolution, or one-sixth(More)