
Distillating Knowledge from Graph Convolutional Networks
Existing knowledge distillation methods focus on convolutional neural ne...
read it

Discrete Laplace Operator Estimation for Dynamic 3D Reconstruction
We present a general paradigm for dynamic 3D reconstruction from multipl...
read it

Learning Latent Space EnergyBased Prior Model
The generator model assumes that the observed example is generated by a ...
read it

Graph Message Passing with Crosslocation Attentions for Longterm ILI Prediction
Forecasting influenzalike illness (ILI) is of prime importance to epide...
read it

AttributeEfficient Learning of Halfspaces with Malicious Noise: NearOptimal Label Complexity and Noise Tolerance
This paper is concerned with computationally efficient learning of homog...
read it

OneBit Compressed Sensing via OneShot Hard Thresholding
This paper concerns the problem of 1bit compressed sensing, where the g...
read it

Learning Deep Generative Models with Short Run Inference Dynamics
This paper studies the fundamental problem of learning deep generative m...
read it

Joint Training of Variational AutoEncoder and Latent EnergyBased Model
This paper proposes a joint training method to learn both the variationa...
read it

Variational Filtering with Copula Models for SLAM
The ability to infer map variables and estimate pose is crucial to the o...
read it

PassGAN: A Deep Learning Approach for Password Guessing
Stateoftheart password guessing tools, such as HashCat and John the R...
read it

A Bootstrap Method for Error Estimation in Randomized Matrix Multiplication
In recent years, randomized methods for numerical linear algebra have re...
read it

Scalable Kernel KMeans Clustering with Nystrom Approximation: RelativeError Bounds
Kernel kmeans clustering can correctly identify and extract a far more ...
read it

Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning
Deep Learning has recently become hugely popular in machine learning, pr...
read it

3D Interest Point Detection via Discriminative Learning
The task of detecting the interest points in 3D meshes has typically bee...
read it

Composition by Conversation
Most musical programming languages are developed purely for coding virtu...
read it

An Amateur Drone Surveillance System Based on Cognitive Internet of Things
Drones, also known as miniunmanned aerial vehicles, have attracted incr...
read it

PedestrianRobot Interaction Experiments in an Exit Corridor
The study of humanrobot interaction (HRI) has received increasing resea...
read it

CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation
Recently, there has been a paradigm shift in stereo matching with learni...
read it

Horizontal Pyramid Matching for Person Reidentification
Despite the remarkable recent progress, person Reidentification (ReID)...
read it

Anchorbased Nearest Class Mean Loss for Convolutional Neural Networks
Discriminative features are critical for machine learning applications. ...
read it

Ocean Plume Tracking with Unmanned Surface Vessels: Algorithms and Experiments
Pollution plume monitoring using autonomous vehicles is important due to...
read it

Effective Automated Decision Support for Managing Crowdtesting
Crowdtesting has grown to be an effective alternative to traditional te...
read it

Crowdtesting : When is The Party Over?
Tradeoffs such as "how much testing is enough" are critical yet challen...
read it

Dual Swap Disentangling
Learning interpretable disentangled representations is a crucial yet cha...
read it

Trajectory Optimization for Cooperative Dualband UAV Swarms
Unmanned aerial vehicles (UAVs) have gained a lot of popularity in diver...
read it

Truth Inference on Sparse Crowdsourcing Data with Local Differential Privacy
Crowdsourcing has arisen as a new problemsolving paradigm for tasks tha...
read it

Wide Activation for Efficient and Accurate Image SuperResolution
In this report we demonstrate that with same parameters and computationa...
read it

Integrity Authentication for SQL Query Evaluation on Outsourced Databases: A Survey
Spurred by the development of cloud computing, there has been considerab...
read it

Costefficient Data Acquisition on Online Data Marketplaces for Correlation Analysis
Incentivized by the enormous economic profits, the data marketplace plat...
read it

Optimal Steerable mmWave Mesh Backhaul Reconfiguration
Future 5G mobile networks will require increased backhaul (BH) capacity ...
read it

Maximum Correntropy DerivativeFree Robust Kalman Filter and Smoother
We consider the problem of robust estimation involving filtering and smo...
read it

Sparse Gaussian Process Temporal Difference Learning for Marine Robot Navigation
We present a method for Temporal Difference (TD) learning that addresses...
read it

A Generic Framework for Task Offloading in mmWave MEC Backhaul Networks
With the emergence of millimeterWave (mmWave) communication technology,...
read it

HandsFree OneTime and Continuous Authentication Using Glass Wearable Devices
Users with limited use of their hands, such as people suffering from dis...
read it

Amalgamating Knowledge towards Comprehensive Classification
With the rapid development of deep learning, there have been an unpreced...
read it

OverSketch: Approximate Matrix Multiplication for the Cloud
We propose OverSketch, an approximate algorithm for distributed matrix m...
read it

A Local Regret in Nonconvex Online Learning
We consider an online learning process to forecast a sequence of outcome...
read it

An Influencebased Clustering Model on Twitter
This paper introduces a temporal framework for detecting and clustering ...
read it

LEPCNN: A Lightweight Edge Device Assisted Privacypreserving CNN Inference Solution for IoT
Supporting convolutional neural network (CNN) inference on resourcecons...
read it

Do Subsampled Newton Methods Work for HighDimensional Data?
Subsampled Newton methods approximate Hessian matrices through subsampli...
read it

Specification and Inference of Trace Refinement Relations
Modern software is constantly changing. Researchers and practitioners ar...
read it

Entropy flow and De Bruijn's identity for a class of stochastic differential equations driven by fractional Brownian motion
Motivated by the classical De Bruijn's identity for the additive Gaussia...
read it

PrivacyPreserving Hierarchical Clustering: Formal Security and Efficient Approximation
Machine Learning (ML) is widely used for predictive tasks in a number of...
read it

Typedbased Relaxed Noninterference for Free
Despite the clear need for specifying and enforcing information flow pol...
read it

The Guided TeamPartitioning Problem: Definition, Complexity, and Algorithm
A long line of literature has focused on the problem of selecting a team...
read it

Federated Multitask Hierarchical Attention Model for Sensor Analytics
Sensors are an integral part of modern Internet of Things (IoT) applicat...
read it

A Direct Approach to Robust Deep Learning Using Adversarial Networks
Deep neural networks have been shown to perform well in many classical m...
read it

Whither Programs as Specifications
Unifying theories distil common features of programming languages and de...
read it

An Incentive Security Model to Provide Fairness for PeertoPeer Networks
PeertoPeer networks are designed to rely on resources of their own use...
read it

Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning
An increasing number of welltrained deep networks have been released on...
read it
Stevens Institute of Technology
Stevens Institute of Technology is a private, coeducational research university in Hoboken, New Jersey.