
-
Deep Paper Gestalt
Recent years have witnessed a significant increase in the number of pape...
read it
-
COR-GAN: Correlation-Capturing Convolutional Neural Networks for Generating Synthetic Healthcare Records
Deep learning models have demonstrated high-quality performance in areas...
read it
-
Differentially Private Synthetic Medical Data Generation using Convolutional GANs
Deep learning models have demonstrated superior performance in several a...
read it
-
Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition
Human activities often occur in specific scene contexts, e.g., playing b...
read it
-
Locally induced Gaussian processes for large-scale simulation experiments
Gaussian processes (GPs) serve as flexible surrogates for complex surfac...
read it
-
Multi-Agent Meta-Reinforcement Learning for Self-Powered and Sustainable Edge Computing Systems
The stringent requirements of mobile edge computing (MEC) applications a...
read it
-
Enforcing Deterministic Constraints on Generative Adversarial Networks for Emulating Physical Systems
Generative adversarial networks (GANs) are initially proposed to generat...
read it
-
Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation
Few-shot classification aims to recognize novel categories with only few...
read it
-
3D Photography using Context-aware Layered Depth Inpainting
We propose a method for converting a single RGB-D input image into a 3D ...
read it
-
Robust Tensor Principal Component Analysis: Exact Recovery via Deterministic Model
Tensor, also known as multi-dimensional array, arises from many applicat...
read it
-
Manifold Graph with Learned Prototypes for Semi-Supervised Image Classification
Recent advances in semi-supervised learning methods rely on estimating c...
read it
-
FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning
Recent state-of-the-art semi-supervised learning (SSL) methods use a com...
read it
-
Acceptable Planning: Influencing Individual Behavior to Reduce Transportation Energy Expenditure of a City
Our research aims at developing intelligent systems to reduce the transp...
read it
-
Neural Abstractive Text Summarization with Sequence-to-Sequence Models
In the past few years, neural abstractive text summarization with sequen...
read it
-
A Closer Look at Few-shot Classification
Few-shot classification aims to learn a classifier to recognize unseen c...
read it
-
DRIT++: Diverse Image-to-Image Translation via Disentangled Representations
Image-to-image translation aims to learn the mapping between two visual ...
read it
-
Distributed Attack-Robust Submodular Maximization for Multi-Robot Planning
We aim to guard swarm-robotics applications against denial-of-service (D...
read it
-
Uncertainty Aware Semi-Supervised Learning on Graph Data
Thanks to graph neural networks (GNNs), semi-supervised node classificat...
read it
-
VideoMatch: Matching based Video Object Segmentation
Video object segmentation is challenging yet important in a wide variety...
read it
-
Deep Transfer Reinforcement Learning for Text Summarization
Deep neural networks are data hungry models and thus they face difficult...
read it
-
Enforcing Statistical Constraints in Generative Adversarial Networks for Modeling Chaotic Dynamical Systems
Simulating complex physical systems often involves solving partial diffe...
read it
-
Gated Recurrent Units Learning for Optimal Deployment of Visible Light Communications Enabled UAVs
In this paper, the problem of optimizing the deployment of unmanned aeri...
read it
-
CPAC-Conv: CP-decomposition to Approximately Compress Convolutional Layers in Deep Learning
Feature extraction for tensor data serves as an important step in many t...
read it
-
Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator
For node level graph encoding, a recent important state-of-art method is...
read it
-
Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space
For a given image generation problem, the intrinsic image manifold is of...
read it
-
Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks
Modeling and forecasting forward citations to a patent is a central task...
read it
-
Lesion Harvester: Iteratively Mining Unlabeled Lesions and Hard-Negative Examples at Scale
Acquiring large-scale medical image data, necessary for training machine...
read it
-
Small Survey Event Detection
A small survey on event detection using Twitter. This work first defines...
read it
-
Multidimensional Uncertainty-Aware Evidential Neural Networks
Traditional deep neural networks (NNs) have significantly contributed to...
read it
-
SAFEBIKE: A Bike-sharing Route Recommender with Availability Prediction and Safe Routing
This paper presents SAFEBIKE, a novel route recommendation system for bi...
read it
-
Mitigating Uncertainty in Document Classification
The uncertainty measurement of classifiers' predictions is especially im...
read it
-
TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction
Critical incident stages identification and reasonable prediction of tra...
read it
-
Robust data assimilation using L_1 and Huber norms
Data assimilation is the process to fuse information from priors, observ...
read it
-
Multimodal Storytelling via Generative Adversarial Imitation Learning
Deriving event storylines is an effective summarization method to succin...
read it
-
Deep Learning for Reliable Mobile Edge Analytics in Intelligent Transportation Systems
Intelligent transportation systems (ITSs) will be a major component of t...
read it
-
Label Efficient Learning of Transferable Representations across Domains and Tasks
We propose a framework that learns a representation transferable across ...
read it
-
Phase Transitions in Image Denoising via Sparsely Coding Convolutional Neural Networks
Neural networks are analogous in many ways to spin glasses, systems whic...
read it
-
Machine Learning for Wireless Networks with Artificial Intelligence: A Tutorial on Neural Networks
Next-generation wireless networks must support ultra-reliable, low-laten...
read it
-
Active Learning for Visual Question Answering: An Empirical Study
We present an empirical study of active learning for Visual Question Ans...
read it
-
Machine Learning for Survival Analysis: A Survey
Accurately predicting the time of occurrence of an event of interest is ...
read it
-
An Improved Modified Cholesky Decomposition Method for Inverse Covariance Matrix Estimation
The modified Cholesky decomposition is commonly used for inverse covaria...
read it
-
Joint Image Filtering with Deep Convolutional Networks
Joint image filters leverage the guidance image as a prior and transfer ...
read it
-
Tracking Persons-of-Interest via Unsupervised Representation Adaptation
Multi-face tracking in unconstrained videos is a challenging problem as ...
read it
-
Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networks
Convolutional neural networks have recently demonstrated high-quality re...
read it
-
Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight
Deep reinforcement learning has shown promising results in learning cont...
read it
-
New Fairness Metrics for Recommendation that Embrace Differences
We study fairness in collaborative-filtering recommender systems, which ...
read it
-
Maximum Volume Inscribed Ellipsoid: A New Simplex-Structured Matrix Factorization Framework via Facet Enumeration and Convex Optimization
Consider a structured matrix factorization scenario where one factor is ...
read it
-
Beyond Parity: Fairness Objectives for Collaborative Filtering
We study fairness in collaborative-filtering recommender systems, which ...
read it
-
C-VQA: A Compositional Split of the Visual Question Answering (VQA) v1.0 Dataset
Visual Question Answering (VQA) has received a lot of attention over the...
read it
-
Why M Heads are Better than One: Training a Diverse Ensemble of Deep Networks
Convolutional Neural Networks have achieved state-of-the-art performance...
read it