
The Devil is in Classification: A Simple Framework for Longtail Instance Segmentation
Most existing object instance detection and segmentation models only wor...
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A MultiLevel Approach to Waste Object Segmentation
We address the problem of localizing waste objects from a color image an...
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Overcoming Classifier Imbalance for Longtail Object Detection with Balanced Group Softmax
Solving longtail large vocabulary object detection with deep learning b...
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Double Circulant Selfdual Codes on Sextic Cyclotomy
This paper contributes to construct double circulant selfdual codes by ...
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Gauntlet: Finding Bugs in Compilers for Programmable Packet Processing
Programmable packetprocessing devices such as programmable switches and...
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Making Robots Draw A Vivid Portrait In Two Minutes
Significant progress has been made with artistic robots. However, existi...
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Human in Events: A LargeScale Benchmark for Humancentric Video Analysis in Complex Events
Along with the development of the modern smart city, humancentric video...
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Automatic lowbit hybrid quantization of neural networks through meta learning
Model quantization is a widely used technique to compress and accelerate...
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StructureLevel Knowledge Distillation For Multilingual Sequence Labeling
Multilingual sequence labeling is a task of predicting label sequences u...
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Discontinuous Galerkin method for a distributed optimal control problem governed by a time fractional diffusion equation
This paper is devoted to the numerical analysis of a control constrained...
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A multiple attributes image quality database for smartphone camera photo quality assessment
Smartphone is the superstar product in digital device market and the qua...
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Numerical analysis of two Galerkin discretizations with graded temporal grids for fractional evolution equations
Two numerical methods with graded temporal grids are analyzed for fracti...
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LargeScale Discrete Fourier Transform on TPUs
In this work, we present a parallel algorithm for largescale discrete F...
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CTM: Collaborative Temporal Modeling for Action Recognition
With the rapid development of digital multimedia, video understanding ha...
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iqiyi Submission to ActivityNet Challenge 2019 Kinetics700 challenge: Hierarchical Groupwise Attention
In this report, the method for the iqiyi submission to the task of Activ...
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Learning a Layout Transfer Network for Context Aware Object Detection
We present a context aware object detection method based on a retrievea...
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Merging External Bilingual Pairs into Neural Machine Translation
As neural machine translation (NMT) is not easily amenable to explicit c...
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Classification Calibration for Longtail Instance Segmentation
Remarkable progress has been made in object instance detection and segme...
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Revisit Knowledge Distillation: a Teacherfree Framework
Knowledge Distillation (KD) aims to distill the knowledge of a cumbersom...
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Scale MLPerf0.6 models on Google TPUv3 Pods
The recent submission of Google TPUv3 Pods to the industry wide MLPerf ...
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DP4coloring of planar graphs with some restrictions on cycles
DPcoloring was introduced by Dvořák and Postle as a generalization of l...
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Open Named Entity Modeling from Embedding Distribution
In this paper, we report our discovery on named entity distribution in g...
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Numerical analysis of a semilinear fractional diffusion equation
This paper considers the numerical analysis of a semilinear fractional d...
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Analysis of a timestepping discontinuous Galerkin method for fractional diffusionwave equation with nonsmooth data
This paper analyzes a timestepping discontinuous Galerkin method for fr...
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Analysis of the L1 scheme for fractional wave equations with nonsmooth data
This paper analyzes the wellknown L1 scheme for fractional wave equatio...
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When Your Friends Become Sellers: An Empirical Study of Social Commerce Site Beidian
Past few years have witnessed the emergence and phenomenal success of st...
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3choosable planar graphs with some precolored vertices and no 5^cycles normally adjacent to 8^cycles
DPcoloring was introduced by Dvořák and Postle [J. Combin. Theory Ser. ...
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Trustable and Automated Machine Learning Running with Blockchain and Its Applications
Machine learning algorithms learn from data and use data from databases ...
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Central Similarity Hashing via Hadamard matrix
Hashing has been widely used for efficient largescale multimedia data r...
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Variable degeneracy on toroidal graphs
Let f be a nonnegative integer valued function on the vertexset of a gr...
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Cover and variable degeneracy
Let f be a nonnegative integer valued function on the vertexset of a gr...
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Distilling Object Detectors with Finegrained Feature Imitation
Stateoftheart CNN based recognition models are often computationally ...
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Prototype Reminding for Continual Learning
Continual learning is a critical ability of continually acquiring and tr...
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A note on 'A fully parallel 3D thinning algorithm and its applications'
A 3D thinning algorithm erodes a 3D binary image layer by layer to extra...
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Fully Automatic Brain Tumor Segmentation using a Normalized Gaussian Bayesian Classifier and 3D Fluid Vector Flow
Brain tumor segmentation from Magnetic Resonance Images (MRIs) is an imp...
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HighPerformance Support Vector Machines and Its Applications
The support vector machines (SVM) algorithm is a popular classification ...
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Fewshot Adaptive Faster RCNN
To mitigate the detection performance drop caused by domain shift, we ai...
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A Unified Analytical Framework for Trustable Machine Learning and Automation Running with Blockchain
Traditional machine learning algorithms use data from databases that are...
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NetKernel: Making Network Stack Part of the Virtualized Infrastructure
This paper presents a system called NetKernel that decouples the network...
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Flash: Efficient Dynamic Routing for Offchain Networks
Offchain networks emerge as a promising solution to address the scalabil...
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Bernstein Polynomial Model for Nonparametric Multivariate Density
In this paper, we study the Bernstein polynomial model for estimating th...
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GMPLL: Graph Matching based Partial Label Learning
Partial Label Learning (PLL) aims to learn from the data where each trai...
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Image Classification at Supercomputer Scale
Deep learning is extremely computationally intensive, and hardware vendo...
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RealTime FineGrained Air Quality Sensing Networks in Smart City: Design, Implementation and Optimization
Driven by the increasingly serious air pollution problem, the monitoring...
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Cluster Pairwise Error Probability and Construction of ParityCheckConcatenated Polar Codes
A successive cancellation list (SCL) decoder with limited list size for ...
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ConvPath: A Software Tool for Lung Adenocarcinoma Digital Pathological Image Analysis Aided by Convolutional Neural Network
The spatial distributions of different types of cells could reveal a can...
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A Selfpaced Regularization Framework for PartialLabel Learning
Partial label learning (PLL) aims to solve the problem where each traini...
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Every toroidal graph without triangles adjacent to 5cycles is DP4colorable
DPcoloring, also known as correspondence coloring, is introduced by Dvo...
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Optimizing Precision for OpenWorld Website Fingerprinting
Traffic analysis attacks to identify which web page a client is browsing...
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UAV Offloading: Spectrum Trading Contract Design for UAV Assisted 5G Networks
Unmanned Aerial Vehicle (UAV) has been recognized as a promising way to ...
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Tao Wang
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MuTao Wang is a Taiwanese mathematician and current professor of mathematics at the University of Columbia.
In 1984, originally for international business, he entered the National University of Taiwan, and after a year he switched to mathematics. He received his B.S. in Mathematics from the National University of Taiwan in 1988 and his M.S. degree from the same institution in 1992. His thesis “Generalized harmonic maps and representations of discrete groups” was awarded by a PhD in Mathematics at Harvard University in 1998. His thesis counselor at Harvard was the Chinese Fields Medalistic and the ShingTung Yau differential geometer.
Wang became an Associate Professor at the Columbia Faculty in 2001 and a full Professor in 2009. Wang was an assistant professor at Stanford University before joining the faculty in Columbia. From 2003–2005 he was a Sloan Research Fellow. In 2007 he was awarded the Chern Prize as the Kavli Fellow of the National Academy of Sciences. In 2010, Wang was a Plenary Speaker in the International Congress of Chinese Mathematicians at the International Congress of Chinese Mathematicians and a Plenary Speaker in the International Congress of mathematical physics at the International Congress on Mathematical Physics. In addition, he also spoke plenary at the International Conference on Differential Geometry in 2011. After winning the Morningside Medal, Wang told interviewers that he wasn’t a very good student and didn’t consistently grade well. It has struggled to study topics that did not only interest him for the grade, but spends a lot of time on topics that interest him. He credits his mathematical career to two persons: his mother and his thesis consultant ShingTung Yau. He cites the support of his mother and understands her decision to change to Mathematics in universities, despite being a considerably less lucrative field, and describes Yau as the pivotal point of his life in 1992 when he decided to focus primarily upon mathematics research.
Wang’s research focuses on differential geometry and mathematical physics and on general relativity in particular. He studied extensively the greater codimensional flow of the mean curvature, leading to criteria for existence, regularity and convergence of the flow. In the field of general relativity, he is known especially for his work on quasilocal mass energy; in his honour, the nearlocal mass of WangYau is named.