
Outlier Detection and Data Clustering via Innovation Search
The idea of Innovation Search was proposed as a data clustering method i...
read it

Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems
Neural networks of ads systems usually take input from multiple resource...
read it

Graph Analysis and Graph Pooling in the Spatial Domain
The spatial convolution layer which is widely used in the Graph Neural N...
read it

CycleSUM: Cycleconsistent Adversarial LSTM Networks for Unsupervised Video Summarization
In this paper, we present a novel unsupervised video summarization model...
read it

A Fourier Analytical Approach to Estimation of Smooth Functions in Gaussian Shift Model
We study the estimation of f() under Gaussian shift model = +, where ∈^d...
read it

Selective Convolutional Network: An Efficient Object Detector with Ignoring Background
It is well known that attention mechanisms can effectively improve the p...
read it

Optimistic Adaptive Acceleration for Optimization
We consider a new variant of AMSGrad. AMSGrad RKK18 is a popular adaptiv...
read it

StructureFeature based Graph Selfadaptive Pooling
Various methods to deal with graph data have been proposed in recent yea...
read it

Logician: A Unified EndtoEnd Neural Approach for OpenDomain Information Extraction
In this paper, we consider the problem of open information extraction (O...
read it

RGBD SLAM in Dynamic Environments Using Points Correlations
This paper proposed a novel RGBD SLAM method for dynamic environments. ...
read it

On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond
The DANE algorithm is an approximate Newton method popularly used for co...
read it

MultiSpectral Visual Odometry without Explicit Stereo Matching
Multispectral sensors consisting of a standard (visiblelight) camera a...
read it

A TwoStage Approach to Multivariate Linear Regression with Sparsely Mismatched Data
A tacit assumption in linear regression is that (response, predictor)pa...
read it

Permutation Recovery from Multiple Measurement Vectors in Unlabeled Sensing
In "Unlabeled Sensing", one observes a set of linear measurements of an ...
read it

Compressed Counting
Counting is among the most fundamental operations in computing. For exam...
read it

Image matting with normalized weight and semisupervised learning
Image matting is an important vision problem. The main stream methods fo...
read it

Tunable GMM Kernels
The recently proposed "generalized minmax" (GMM) kernel can be efficien...
read it

Generalized Intersection Kernel
Following the very recent line of work on the "generalized minmax" (GMM...
read it

L2GSCI: Local to Global Seam Cutting and Integrating for Accurate Face Contour Extraction
Current face alignment algorithms can robustly find a set of landmarks a...
read it

Nystrom Method for Approximating the GMM Kernel
The GMM (generalized minmax) kernel was recently proposed (Li, 2016) as...
read it

Linearized GMM Kernels and Normalized Random Fourier Features
The method of "random Fourier features (RFF)" has become a popular tool ...
read it

A Tight Bound of Hard Thresholding
This paper is concerned with the hard thresholding technique which sets ...
read it

A Comparison Study of Nonlinear Kernels
In this paper, we compare 5 different nonlinear kernels: minmax, RBF, f...
read it

Constrained LowRank Learning Using Least SquaresBased Regularization
Lowrank learning has attracted much attention recently due to its effic...
read it

2Bit Random Projections, NonLinear Estimators, and Approximate Near Neighbor Search
The method of random projections has become a standard tool for machine ...
read it

Sign Stable Random Projections for LargeScale Learning
We study the use of "sign αstable random projections" (where 0<α≤ 2) fo...
read it

Regularizationfree estimation in trace regression with symmetric positive semidefinite matrices
Over the past few years, trace regression models have received considera...
read it

Efficient Online Minimization for LowRank Subspace Clustering
Lowrank representation (LRR) has been a significant method for segmenti...
read it

MinMax Kernels
The minmax kernel is a generalization of the popular resemblance kernel...
read it

Asymmetric Minwise Hashing
Minwise hashing (Minhash) is a widely popular indexing scheme in practic...
read it

Improved Asymmetric Locality Sensitive Hashing (ALSH) for Maximum Inner Product Search (MIPS)
Recently it was shown that the problem of Maximum Inner Product Search (...
read it

In Defense of MinHash Over SimHash
MinHash and SimHash are the two widely adopted Locality Sensitive Hashin...
read it

Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS)
We present the first provably sublinear time algorithm for approximate M...
read it

CoRE Kernels
The term "CoRE kernel" stands for correlationresemblance kernel. In man...
read it

Graph Kernels via Functional Embedding
We propose a representation of graph as a functional object derived from...
read it

A New Space for Comparing Graphs
Finding a new mathematical representations for graph, which allows direc...
read it

Multilabel ensemble based on variable pairwise constraint projection
Multilabel classification has attracted an increasing amount of attenti...
read it

Adaptive Stochastic Alternating Direction Method of Multipliers
The Alternating Direction Method of Multipliers (ADMM) has been studied ...
read it

Gradient Hard Thresholding Pursuit for SparsityConstrained Optimization
Hard Thresholding Pursuit (HTP) is an iterative greedy selection procedu...
read it

Learning Pairwise Graphical Models with Nonlinear Sufficient Statistics
We investigate a generic problem of learning pairwise exponential family...
read it

Exact Sparse Recovery with L0 Projections
Many applications concern sparse signals, for example, detecting anomali...
read it

ABCLogitBoost for Multiclass Classification
We develop abclogitboost, based on the prior work on abcboost and robu...
read it

Object Proposal with Kernelized Partial Ranking
Object proposals are an ensemble of bounding boxes with high potential t...
read it

One Permutation Hashing for Efficient Search and Learning
Recently, the method of bbit minwise hashing has been applied to large...
read it

Improving Compressed Counting
Compressed Counting (CC) [22] was recently proposed for estimating the a...
read it

Robust LogitBoost and Adaptive Base Class (ABC) LogitBoost
Logitboost is an influential boosting algorithm for classification. In t...
read it

Approximating HigherOrder Distances Using Random Projections
We provide a simple method and relevant theoretical analysis for efficie...
read it

Training Logistic Regression and SVM on 200GB Data Using bBit Minwise Hashing and Comparisons with Vowpal Wabbit (VW)
We generated a dataset of 200 GB with 10^9 features, to test our recent ...
read it

Accurate Estimators for Improving Minwise Hashing and bBit Minwise Hashing
Minwise hashing is the standard technique in the context of search and d...
read it

Hashing Algorithms for LargeScale Learning
In this paper, we first demonstrate that bbit minwise hashing, whose es...
read it