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Proceedings of the 2020 SIAM International Conference on Data Mining
Learning a Neural-network-based Representation for Open Set Recognition
monograph
Author(s):
Mehadi Hassen
,
Philip K. Chan
Publication date
(Online):
March 26 2020
Publisher:
Society for Industrial and Applied Mathematics
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Value-based Healthcare
Author and book information
Book Chapter
Publication date (Print):
January 2020
Publication date (Online):
March 26 2020
Pages
: 154-162
DOI:
10.1137/1.9781611976236.18
SO-VID:
e3c3e073-fc21-4946-8328-9144e12d6c8e
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Book chapters
pp. 1
LTSpAUC: Learning Time-series Shapelets for Optimizing Partial AUC
pp. 10
Two-Sample Testing for Event Impacts in Time Series
pp. 19
Knowledge guided diagnosis prediction via graph spatial-temporal network
pp. 28
Convolutional Methods for Predictive Modeling of Geospatial Data
pp. 37
Pattern detection in large temporal graphs using algebraic fingerprints
pp. 46
Filling Missing Values on Wearable-Sensory Time Series Data
pp. 55
Meta-Learning for Size and Fit Recommendation in Fashion
pp. 64
BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network
pp. 73
Stacked Mixed-Order Graph Convolutional Networks for Collaborative Filtering
pp. 82
BiGAN: Collaborative Filtering with Bidirectional Generative Adversarial Networks
pp. 91
Multiplex Memory Network for Collaborative Filtering
pp. 100
Content-Aware Successive Point-of-Interest Recommendation
pp. 109
Deep Multi-sphere Support Vector Data Description
pp. 118
Finding the Sweet Spot: Batch Selection for One-Class Active Learning
pp. 127
“Now you see it, now you don't!” Detecting Suspicious Pattern Absences in Continuous Time Series
pp. 136
Semantic Discord: Finding Unusual Local Patterns for Time Series
pp. 145
Exploring the Unknown – Query Synthesis in One-Class Active Learning
pp. 154
Learning a Neural-network-based Representation for Open Set Recognition
pp. 163
Two-variable Dual Coordinate Descent Methods for Linear SVM with/without the Bias Term
pp. 172
A Predictive Optimization Framework for Hierarchical Demand Matching
pp. 181
Dual Coordinate-Descent Methods for Linear One-Class SVM and SVDD
pp. 190
Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization
pp. 199
Second-order Optimization for Non-convex Machine Learning: an Empirical Study
pp. 208
DANR: Discrepancy-aware Network Regularization
pp. 217
An Advantage Actor-Critic Algorithm with Confidence Exploration for Open Information Extraction
pp. 226
What Do Questions Exactly Ask? MFAE: Duplicate Question Identification with Multi-Fusion Asking Emphasis
pp. 235
Identifying Potential Investors with Data Driven Approaches
pp. 244
Document Clustering Meets Topic Modeling with Word Embeddings
pp. 253
Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data
pp. 262
SSNN: Sentiment Shift Neural Network
pp. 271
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data
pp. 280
A Graph-Based Approach for Active Learning in Regression
pp. 289
On Supervised Change Detection in Graph Streams
pp. 298
Optimal Bidding Strategy without Exploration in Real-time Bidding
pp. 307
Global-and-Local Aware Data Generation for the Class Imbalance Problem
pp. 316
Harmonic Alignment
pp. 325
Residual Core Maximization: An Efficient Algorithm for Maximizing the Size of the k-Core
pp. 334
Deep Matrix Tri-Factorization: Mining Vertex-wise Interactions in Multi-Space Attributed Graphs
pp. 343
Adiabatic Quantum Computing for Max-Sum Diversification
pp. 352
Deep Adversarial Canonical Correlation Analysis
pp. 361
Deep Self-representative Concept Factorization Network for Representation Learning
pp. 370
Deep Neural Networks with Knowledge Instillation
pp. 379
Dual-Attention Recurrent Networks for Affine Registration of Neuroimaging Data
pp. 388
Efficient and Effective Graph Convolution Networks
pp. 397
HIDRA: Head Initialization across Dynamic targets for Robust Architectures
pp. 406
Cost-Effective and Stable Policy Optimization Algorithm for Uplift Modeling with Multiple Treatments
pp. 415
Well-calibrated and specialized probability estimation trees
pp. 424
Bayesian Modeling of Intersectional Fairness: The Variance of Bias
pp. 433
An Instance-Specific Algorithm for Learning the Structure of Causal Bayesian Networks Containing Latent Variables
pp. 442
Features or Shape? Tackling the False Dichotomy of Time Series Classification
pp. 451
Attention-Aware Answers of the Crowd
pp. 460
HYPA: Efficient Detection of Path Anomalies in Time Series Data on Networks
pp. 469
Fisher Deep Domain Adaptation
pp. 478
Representation Learning for Imbalanced Cross-Domain Classification
pp. 487
A Unified Non-Negative Matrix Factorization Framework for Semi Supervised Learning on Graphs
pp. 496
Temporal Graph Kernels for Classifying Dissemination Processes
pp. 505
Heavy-Tailed Universality Predicts Trends in Test Accuracies for Very Large Pre-Trained Deep Neural Networks
pp. 514
Rare Disease Prediction by Generating Quality-Assured Electronic Health Records
pp. 523
Dissecting Ethereum Blockchain Analytics: What We Learn from Topology and Geometry of the Ethereum Graph?
pp. 532
Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling
pp. 541
D2M: Dynamic Defense and Modeling of Adversarial Movement in Networks
pp. 550
Detecting Media Self-Censorship without Explicit Training Data
pp. 559
PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly
pp. 568
Improved mixing time for k-subgraph sampling
pp. 577
SPADE: Streaming PARAFAC2 DEcomposition for Large Datasets
pp. 586
Explainable Subgraphs with Surprising Densities: A Subgroup Discovery Approach
pp. 595
Vertex-reinforced Random Walk for Network Embedding
pp. 604
GRIA: Graphical Regularization for Integrative Analysis
pp. 613
On the Information Unfairness of Social Networks
pp. 622
Lag-Aware Multivariate Time-Series Segmentation
pp. 631
Deep Parametric Model for Discovering Group-cohesive Functional Brain Regions
pp. 640
Deep Kernel Learning for Clustering
pp. 649
Maximizing diversity over clustered data
pp. 658
Heterogeneous Dual-Task Clustering with Visual-Textual Information
pp. 667
NSVD: Normalized Singular Value Deviation Reveals Number of Latent Factors in Tensor Decomposition
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