
Revisit Knowledge Distillation: a Teacherfree Framework
Knowledge Distillation (KD) aims to distill the knowledge of a cumbersom...
read it

Fewshot Adaptive Faster RCNN
To mitigate the detection performance drop caused by domain shift, we ai...
read it

Classification Calibration for Longtail Instance Segmentation
Remarkable progress has been made in object instance detection and segme...
read it

HighPerformance Support Vector Machines and Its Applications
The support vector machines (SVM) algorithm is a popular classification ...
read it

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...
read it

Scale MLPerf0.6 models on Google TPUv3 Pods
The recent submission of Google TPUv3 Pods to the industry wide MLPerf ...
read it

Learning a Layout Transfer Network for Context Aware Object Detection
We present a context aware object detection method based on a retrievea...
read it

GMPLL: Graph Matching based Partial Label Learning
Partial Label Learning (PLL) aims to learn from the data where each trai...
read it

Prototype Reminding for Continual Learning
Continual learning is a critical ability of continually acquiring and tr...
read it

Distilling Object Detectors with Finegrained Feature Imitation
Stateoftheart CNN based recognition models are often computationally ...
read it

Central Similarity Hashing via Hadamard matrix
Hashing has been widely used for efficient largescale multimedia data r...
read it

Trustable and Automated Machine Learning Running with Blockchain and Its Applications
Machine learning algorithms learn from data and use data from databases ...
read it

CTM: Collaborative Temporal Modeling for Action Recognition
With the rapid development of digital multimedia, video understanding ha...
read it

Convolutional Neural Networks over Tree Structures for Programming Language Processing
Programming language processing (similar to natural language processing)...
read it

A Multiparent Memetic Algorithm for the Linear Ordering Problem
In this paper, we present a multiparent memetic algorithm (denoted by M...
read it

Driverseat: Crowdstrapping Learning Tasks for Autonomous Driving
While emerging deeplearning systems have outclassed knowledgebased app...
read it

An Empirical Evaluation of Deep Learning on Highway Driving
Numerous groups have applied a variety of deep learning techniques to co...
read it

UAV Offloading: Spectrum Trading Contract Design for UAV Assisted Offloading in Cellular Networks
Unmanned Aerial Vehicle (UAV) has been recognized as a promising way to ...
read it

UAV Offloading: Spectrum Trading Contract Design for UAV Assisted 5G Networks
Unmanned Aerial Vehicle (UAV) has been recognized as a promising way to ...
read it

Optimizing Precision for OpenWorld Website Fingerprinting
Traffic analysis attacks to identify which web page a client is browsing...
read it

A Selfpaced Regularization Framework for PartialLabel Learning
Partial label learning (PLL) aims to solve the problem where each traini...
read it

Every toroidal graph without triangles adjacent to 5cycles is DP4colorable
DPcoloring, also known as correspondence coloring, is introduced by Dvo...
read it

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...
read it

Cluster Pairwise Error Probability and Construction of ParityCheckConcatenated Polar Codes
A successive cancellation list (SCL) decoder with limited list size for ...
read it

Image Classification at Supercomputer Scale
Deep learning is extremely computationally intensive, and hardware vendo...
read it

RealTime FineGrained Air Quality Sensing Networks in Smart City: Design, Implementation and Optimization
Driven by the increasingly serious air pollution problem, the monitoring...
read it

NetKernel: Making Network Stack Part of the Virtualized Infrastructure
This paper presents a system called NetKernel that decouples the network...
read it

Bernstein Polynomial Model for Nonparametric Multivariate Density
In this paper, we study the Bernstein polynomial model for estimating th...
read it

Flash: Efficient Dynamic Routing for Offchain Networks
Offchain networks emerge as a promising solution to address the scalabil...
read it

A Unified Analytical Framework for Trustable Machine Learning and Automation Running with Blockchain
Traditional machine learning algorithms use data from databases that are...
read it

Cover and variable degeneracy
Let f be a nonnegative integer valued function on the vertexset of a gr...
read it

Analysis of a timestepping discontinuous Galerkin method for fractional diffusionwave equation with nonsmooth data
This paper analyzes a timestepping discontinuous Galerkin method for fr...
read it

Analysis of the L1 scheme for fractional wave equations with nonsmooth data
This paper analyzes the wellknown L1 scheme for fractional wave equatio...
read it

Numerical analysis of a semilinear fractional diffusion equation
This paper considers the numerical analysis of a semilinear fractional d...
read it

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...
read it

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...
read it

Variable degeneracy on toroidal graphs
Let f be a nonnegative integer valued function on the vertexset of a gr...
read it

Open Named Entity Modeling from Embedding Distribution
In this paper, we report our discovery on named entity distribution in g...
read it

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...
read it

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. ...
read it

Merging External Bilingual Pairs into Neural Machine Translation
As neural machine translation (NMT) is not easily amenable to explicit c...
read it

DP4coloring of planar graphs with some restrictions on cycles
DPcoloring was introduced by Dvořák and Postle as a generalization of l...
read it

LargeScale Discrete Fourier Transform on TPUs
In this work, we present a parallel algorithm for largescale discrete F...
read it
Tao Wang
is this you? claim profile
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.