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Adversarial Canonical Correlation Analysis
Canonical Correlation Analysis (CCA) is a statistical technique used to ...
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Is AI different for SE?
What AI tools are needed for SE? Ideally, we should have simple rules th...
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Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices
Mobile devices are becoming an important carrier for deep learning tasks...
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Towards Interpretable Image Synthesis by Learning Sparsely Connected AND-OR Networks
This paper proposes interpretable image synthesis by learning hierarchic...
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Pose Guided Fashion Image Synthesis Using Deep Generative Model
Generating a photorealistic image with intended human pose is a promisin...
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Street Scene: A new dataset and evaluation protocol for video anomaly detection
Progress in video anomaly detection research is currently slowed by smal...
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Flow Models for Arbitrary Conditional Likelihoods
Understanding the dependencies among features of a dataset is at the cor...
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Deep Transform and Metric Learning Network: Wedding Deep Dictionary Learning and Neural Networks
On account of its many successes in inference tasks and denoising applic...
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Local Clustering with Mean Teacher for Semi-supervised Learning
The Mean Teacher (MT) model of Tarvainen and Valpola has shown favorable...
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Learning Spatial Pyramid Attentive Pooling in Image Synthesis and Image-to-Image Translation
Image synthesis and image-to-image translation are two important generat...
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How to "DODGE" Complex Software Analytics?
AI software is still software. Software engineers need better tools to m...
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ARCHER: Aggressive Rewards to Counter bias in Hindsight Experience Replay
Experience replay is an important technique for addressing sample-ineffi...
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Interactive Learning of Environment Dynamics for Sequential Tasks
In order for robots and other artificial agents to efficiently learn to ...
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Analysis Dictionary Learning based Classification: Structure for Robustness
A discriminative structured analysis dictionary is proposed for the clas...
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Holistically-Attracted Wireframe Parsing
This paper presents a fast and parsimonious parsing method to accurately...
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3D Virtual Garment Modeling from RGB Images
We present a novel approach that constructs 3D virtual garment models fr...
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Auto-Context R-CNN
Region-based convolutional neural networks (R-CNN) fast_rcnn,faster_rcnn...
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Better Technical Debt Detection via SURVEYing
Software analytics can be improved by surveying; i.e. rechecking and (po...
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Adversarial Distillation for Ordered Top-k Attacks
Deep Neural Networks (DNNs) are vulnerable to adversarial attacks, espec...
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The Secant-Newton Map is Optimal Among Contracting n^th Degree Maps for n^th Root Computation
Consider the problem: given a real number x and an error bound ϵ, find a...
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Delay Optimal Scheduling for Energy Harvesting Based Communications
Green communication attracts increasing research interest recently. Equi...
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Generalized Linear Model Regression under Distance-to-set Penalties
Estimation in generalized linear models (GLM) is complicated by the pres...
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AOGNets: Deep AND-OR Grammar Networks for Visual Recognition
This paper presents a method of learning deep AND-OR Grammar (AOG) netwo...
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Interpretable R-CNN
This paper presents a method of learning qualitatively interpretable mod...
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Scene-centric Joint Parsing of Cross-view Videos
Cross-view video understanding is an important yet under-explored area i...
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Tosca: Operationalizing Commitments Over Information Protocols
The notion of commitment is widely studied as a high-level abstraction f...
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Variational Gaussian Approximation for Poisson Data
The Poisson model is frequently employed to describe count data, but in ...
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Effective Connectivity-Based Neural Decoding: A Causal Interaction-Driven Approach
We propose a geometric model-free causality measurebased on multivariate...
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Fast Incremental SVDD Learning Algorithm with the Gaussian Kernel
Support vector data description (SVDD) is a machine learning technique t...
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Blue Sky Ideas in Artificial Intelligence Education from the EAAI 2017 New and Future AI Educator Program
The 7th Symposium on Educational Advances in Artificial Intelligence (EA...
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Learning Gaussian Graphical Models Using Discriminated Hub Graphical Lasso
We develop a new method called Discriminated Hub Graphical Lasso (DHGL) ...
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Algorithms for Fitting the Constrained Lasso
We compare alternative computing strategies for solving the constrained ...
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Going off the Grid: Iterative Model Selection for Biclustered Matrix Completion
We consider the problem of performing matrix completion with side inform...
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Why is Differential Evolution Better than Grid Search for Tuning Defect Predictors?
Context: One of the black arts of data mining is learning the magic para...
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Shape Constrained Tensor Decompositions using Sparse Representations in Over-Complete Libraries
We consider N-way data arrays and low-rank tensor factorizations where t...
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An Attention-Driven Approach of No-Reference Image Quality Assessment
In this paper, we present a novel method of no-reference image quality a...
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Zero-Shot Learning posed as a Missing Data Problem
This paper presents a method of zero-shot learning (ZSL) which poses ZSL...
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Object Detection via Aspect Ratio and Context Aware Region-based Convolutional Networks
Jointly integrating aspect ratio and context has been extensively studie...
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Low-Autocorrelation Binary Sequences: On Improved Merit Factors and Runtime Predictions to Achieve Them
The search for binary sequences with a high figure of merit, known as th...
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Modularity Component Analysis versus Principal Component Analysis
In this paper the exact linear relation between the leading eigenvectors...
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Classification and regression using an outer approximation projection-gradient method
This paper deals with sparse feature selection and grouping for classifi...
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Relations Between Adjacency and Modularity Graph Partitioning
In this paper the exact linear relation between the leading eigenvector ...
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Face Detection with End-to-End Integration of a ConvNet and a 3D Model
This paper presents a method for face detection in the wild, which integ...
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Robust Topological Feature Extraction for Mapping of Environments using Bio-Inspired Sensor Networks
In this paper, we exploit minimal sensing information gathered from biol...
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Multi-Level Anomaly Detection on Time-Varying Graph Data
This work presents a novel modeling and analysis framework for graph seq...
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Determining the Number of Clusters via Iterative Consensus Clustering
We use a cluster ensemble to determine the number of clusters, k, in a g...
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Convex Biclustering
In the biclustering problem, we seek to simultaneously group observation...
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Algorithms, Initializations, and Convergence for the Nonnegative Matrix Factorization
It is well known that good initializations can improve the speed and acc...
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Sequential Advantage Selection for Optimal Treatment Regimes
Variable selection for optimal treatment regime in a clinical trial or a...
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Bayesian Neural Networks for Genetic Association Studies of Complex Disease
Discovering causal genetic variants from large genetic association studi...
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