Author
Yi Chen
Other affiliations: Rochester Institute of Technology, National Institutes of Health, Columbia University ...read more
Bio: Yi Chen is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Large Hadron Collider & Medicine. The author has an hindex of 217, co-authored 4342 publications receiving 293080 citations. Previous affiliations of Yi Chen include Rochester Institute of Technology & National Institutes of Health.
Topics: Large Hadron Collider, Medicine, Physics, Lepton, Higgs boson
Papers published on a yearly basis
Papers
More filters
•
TL;DR: In this paper, a general sparse-with-dense matrix multiplication implementation for convolution of feature maps with kernels of arbitrary sparsity patterns is presented. And a performance model is developed to predict the sweet spots of sparsity levels for different layers and on different computer architectures.
Abstract: Phenomenally successful in practical inference problems, convolutional neural networks (CNN) are widely deployed in mobile devices, data centers, and even supercomputers The number of parameters needed in CNNs, however, are often large and undesirable Consequently, various methods have been developed to prune a CNN once it is trained Nevertheless, the resulting CNNs offer limited benefits While pruning the fully connected layers reduces a CNN's size considerably, it does not improve inference speed noticeably as the compute heavy parts lie in convolutions Pruning CNNs in a way that increase inference speed often imposes specific sparsity structures, thus limiting the achievable sparsity levels
We present a method to realize simultaneously size economy and speed improvement while pruning CNNs Paramount to our success is an efficient general sparse-with-dense matrix multiplication implementation that is applicable to convolution of feature maps with kernels of arbitrary sparsity patterns Complementing this, we developed a performance model that predicts sweet spots of sparsity levels for different layers and on different computer architectures Together, these two allow us to demonstrate 31--73$\times$ convolution speedups over dense convolution in AlexNet, on Intel Atom, Xeon, and Xeon Phi processors, spanning the spectrum from mobile devices to supercomputers We also open source our project at this https URL
128 citations
••
05 Mar 2014
TL;DR: In this article, double parton scattering was investigated in proton-proton collisions at 7 TeV where the final state includes a W boson which decays into a muon and a neutrino, and two jets.
Abstract: Double parton scattering is investigated in proton-proton collisions at sqrt(s) = 7 TeV where the final state includes a W boson, which decays into a muon and a neutrino, and two jets. The data sample corresponds to an integrated luminosity of 5 inverse femtobarns, collected with the CMS detector at the LHC. Observables sensitive to double parton scattering are investigated after being corrected for detector effects and selection efficiencies. The fraction of W + 2-jet events due to double parton scattering is measured to be 0.055 +/- 0.002 (stat.) +/- 0.014 (syst.). The effective cross section, sigma[eff], characterizing the effective transverse area of hard partonic interactions in collisions between protons is measured to be 20.7 +/- 0.8 (stat.) +/- 6.6 (syst.) mb.
128 citations
••
TL;DR: In this paper, the local electronic properties of single-and few-layer 1T-TaSe2 via spatial and momentum-resolved spectroscopy involving scanning tunnelling microscopy and angleresolved photoemission were investigated.
Abstract: Strong electron correlation can induce Mott insulating behaviour and produce intriguing states of matter such as unconventional superconductivity and quantum spin liquids. Recent advances in van der Waals material synthesis enable the exploration of Mott systems in the two-dimensional limit. Here we report characterization of the local electronic properties of single- and few-layer 1T-TaSe2 via spatial- and momentum-resolved spectroscopy involving scanning tunnelling microscopy and angle-resolved photoemission. Our results indicate that electron correlation induces a robust Mott insulator state in single-layer 1T-TaSe2 that is accompanied by unusual orbital texture. Interlayer coupling weakens the insulating phase, as shown by reduction of the energy gap and quenching of the correlation-driven orbital texture in bilayer and trilayer 1T-TaSe2. This establishes single-layer 1T-TaSe2 as a useful platform for investigating strong correlation physics in two dimensions. The electrons that contribute to the Mott insulator state in single-layer 1T-TaSe2 are shown to also have a rich variation in their orbital occupation. As more layers are added, both the insulating state and orbital texture weaken.
128 citations
••
TL;DR: In this article, a peaking structure in the J/psi phi mass spectrum near threshold was observed in B(+/-) to J/Psi K(−)-decays, produced in pp collisions at sqrt(s) = 7 TeV collected with the CMS detector at the LHC.
128 citations
••
TL;DR: In this article, the authors measured the centrality and rapidity dependence of jet production in TeV proton-lead collisions and the jet cross-section in $\sqrt{s} = 2.76$.
127 citations
Cited by
More filters
••
[...]
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.
Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …
33,785 citations
•
28,685 citations
••
TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
Abstract: Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules. The major component of KEGG is the PATHWAY database that consists of graphical diagrams of biochemical pathways including most of the known metabolic pathways and some of the known regulatory pathways. The pathway information is also represented by the ortholog group tables summarizing orthologous and paralogous gene groups among different organisms. KEGG maintains the GENES database for the gene catalogs of all organisms with complete genomes and selected organisms with partial genomes, which are continuously re-annotated, as well as the LIGAND database for chemical compounds and enzymes. Each gene catalog is associated with the graphical genome map for chromosomal locations that is represented by Java applet. In addition to the data collection efforts, KEGG develops and provides various computational tools, such as for reconstructing biochemical pathways from the complete genome sequence and for predicting gene regulatory networks from the gene expression profiles. The KEGG databases are daily updated and made freely available (http://www.genome.ad.jp/kegg/).
24,024 citations
••
TL;DR: The philosophy and design of the limma package is reviewed, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
22,147 citations
••
TL;DR: Atherosclerosis is an inflammatory disease as discussed by the authors, and it is a major cause of death in the United States, Europe, and much of Asia, despite changes in lifestyle and use of new pharmacologic approaches to lower plasma cholesterol concentrations.
Abstract: Atherosclerosis is an inflammatory disease. Because high plasma concentrations of cholesterol, in particular those of low-density lipoprotein (LDL) cholesterol, are one of the principal risk factors for atherosclerosis,1 the process of atherogenesis has been considered by many to consist largely of the accumulation of lipids within the artery wall; however, it is much more than that. Despite changes in lifestyle and the use of new pharmacologic approaches to lower plasma cholesterol concentrations,2,3 cardiovascular disease continues to be the principal cause of death in the United States, Europe, and much of Asia.4,5 In fact, the lesions of atherosclerosis represent . . .
19,881 citations