D3M Academic Papers

AutoML User Interfaces

Towards Evaluating Exploratory Model Building Process with AutoML Systems
NYU/UTD/Uncharted; Keywords: Human-guided machine learning; Evaluation Methodology; System Evaluation; Machine Learning; Automated Machine Learning; AutoML; Exploratory Visual Analysis; Exploratory Model Building

Towards Human-Guided Machine Learning
ISI/Harvard/UTD; Keywords: Human-guided machine learning; Automated machine learning (AutoML); Task analysis; Scientific workflows.

Distil: A Mixed-Initiative Model Discovery System for Subject Matter Experts
Uncharted; Keywords: Augmented Intelligence;Machine Learning;Mixed-initiative;Visual Analytics

PipelineProfiler: A Visual Analytics Tool for the Exploration of AutoML Pipelines
NYU; Keywords: Automatic Machine Learning; Pipeline Visualization; Model Evaluation

AutoML Engines

MetaTPOT: Enhancing A Tree-based Pipeline Optimization Tool Using Meta-Learning
UC Berkeley; Keywords: AutoML; Meta-Learning; Genetic Programming(GP); TPOT

Metalearning by Exploiting Granular Machine Learning Pipeline Metadata
BYU; Keywords: metalearning;automl;ml pipeline;metamodel;meta-dataset;metafeatures

Modeling and Forecasting Armed Conflict: AutoML with Human-Guided Machine Learning
Harvard/UTD; Keywords: Human-guided machine learning; Automated machine learning (AutoML); conflict forecasting.

On Robustness of Neural Architecture Search under Label Noise.
TAMU; Keywords: deep learning; automated machine learning; neuralarchitecture search; label noise; robust lossfunction

P4ML: A phased performance-based pipeline planner for automated machine learning
ISI; Keywords: Automating machine learning, planning, pipelines, workflows, AutoML

Preprocessor Selection for Machine Learning Pipelines
BYU; Keywords: metalearning;preprocessor selection;ml pipeline design;automl

RankML: a Meta Learning-Based Approach for Pre-Ranking Machine Learning Pipelines
UC Berkeley; Keywords: AutoML; meta-learning; machine learning pipelines

A Hybrid Approach for Automatic Model Recommendation
UC Berkeley; Keywords: Classification; Classifier Families; Meta-Learning; Dataset Metafeatures; Scholarly Big Data; Algorithm Recommendation; Word Embedding; Expert System

Auto-Keras: An Efficient Neural Architecture Search System
TAMU; Keywords: Automated Machine Learning; AutoML; Neural Architecture Search; Bayesian Optimization; Network Morphism

AutoGRD: Model Recommendation Through Graphical Dataset Representation
UC Berkeley; Awards: Best paper award CIKM '19; Best industry paper award CIKM '19; Keywords: Meta-learning; Algorithm selection; AutoML; Dataset representation; Classification; Regression; Graph embedding

Automatic Machine Learning Derived from Scholarly Big Data
UC Berkeley; Keywords: Meta-learning; Algorithm selection; AutoML; Dataset representation; Classification;


Joint Embedding of Graphs
JHU; Keywords: graphs, embedding, feature extraction, statistical inference

Knowledge Augmented Deep Neural Networks for Joint Facial Expression and Action Unit Recognition
RPI; Keywords: computer vision; facial expression and action unites; prior knowledge

Label Error Correction and Generation Through Label Relationships
RPI; Keywords: Bayesian network, structure learning, and label denoising

On a 'Two Truths' Phenomenon in Spectral Graph Clustering
JHU; Keywords: Spectral Embedding, Spectral Clustering, Graph, Network, Connectome

On consistent vertex nomination schemes
JHU; Keywords: vertex nomination, Bayes optimal

On estimation and inference in latent structure random graphs
JHU; Keywords: efficiency, Latent structure random graphs, manifold learning, spectral graph inference

On spectral embedding performance and elucidating network structure in stochastic block model graphs
JHU; Keywords: Statistical network analysis; random graphs; stochastic block model; Laplacian spectral embed- ding; adjacency spectral embedding; Chernoff information; vertex clustering.

Seeded Graph Matching
JHU; Keywords: Hungarian Algorithm, Quadratic Assignment Problem (QAP), Vertex Alignment

Signal-plus-noise matrix models: eigenvector deviations and fluctuations
JHU; Keywords: Random matrix; Signal-plus-noise; Eigenvector perturbation; Principal component analysis; Asymptotic normality.

Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering
JHU; Keywords: Adjacency spectral embedding, Model-based clustering, Stochastic block model

The two-to-infinity norm and singular subspace geometry with applications to high-dimensional statistics
JHU; Keywords: singular value decomposition, principal component analysis, eigenvector perturbation, spectral methods, Procrustes analysis, high-dimensional statis- tics

Type-augmented Relation Prediction in Knowledge Graphs
RPI; Keywords: prior knowledge, relation prediction, knowledge graph

Vertex Nomination Via Seeded Graph Matching
JHU; Keywords: vertex nomination, graph matching, seeded graph matching, graph inference, graph mining, stochastic block model

Vertex Nomination, Consistent Estimation, and Adversarial Modification
JHU; Keywords: adversarial machine learning, networks, Random graphs, statistics, Vertex nomination

Vertex nomination: The canonical sampling and the extended spectral nomination schemes
JHU; Keywords: vertex nomination, Markov chain Monte Carlo, spectral partitioning, Mclust

Abstractive Tabular Dataset Summarization via Knowledge Base Semantic Embeddings
Uncharted; Keywords: Dataset Summarization;Type Recommendation;Semantic Embeddings

Alignment Strength and Correlation for Graphs
JHU; Keywords: correlated Bernoulli random graphs, alignment strength, graph correlation, graph matchability, complexity of graph matching

Amortized Monte Carlo Integration
UBC; Awards: Best Paper Honourable Mention ICML 2019

Blendshape-augmented Facial Action Units Detection
RPI; Keywords: computer vision; facial action units; 3D facial blendshapes

Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
UBC; Awards: Best Paper Finalist at Supercomputing 2019

Forecasting Hierarchical Time Series with a Regularized Embedding Space
Uncharted; Keywords: hierarchical time series; grouped time series; time series forecasting; embedding space; neural network

Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning
ISI; Keywords: Graph, Learning, Algorithm, Scale, Message Passing, Node Embeddings

AutoML Infrastructure


Missing Value Imputation for Mixed Data Through Gaussian Copula
Cornell University; Keywords: mixed data; ordinal data; Gaussian copula; missing values; imputation

OBOE: Collaborative Filtering for AutoML Model Selection
Cornell University; Keywords: AutoML; meta-learning; time-constrained; model selection; collaborative filtering

Ordalia: Deep Learning Hyperparameter Search via Generalization Error Bounds Extrapolation
MIT/Brown; Keywords: Deep Learning, Hyperparameters Optimization, Multi-armed Bandits, Automated Machine Learning

Techniques for Automated Machine Learning
TAMU; Keywords: automated machine learning; neural architecture search; bayesian optimization; reinforce-ment learning; evolutionary algorithm; gradient-based methods

Third-Party Data Providers Ruin Simple Mechanisms
UBC (Hebrew University of Jerusalem)

Towards Automated Neural Architecture Discovering for Click-Through Rate Prediction
TAMU; Keywords: Information systems; Recommender systems; Theory of computation; Evolutionary algorithms; Computing methodologies; Neural networks

Understanding Spatio-Temporal Urban Processes
NYU; Keywords: data quality;data profiling;urban data

A Survey on Collecting, Managing, and Analyzing Provenance from Scripts
NYU; Keywords: provenance;scripts;collecting;managing;analyzing;survey

Annealed Importance Sampling with q-Paths
ISI; Awards: Best Paper Award: NeurIPS Workshop on Deep Learning through Information Geometry

AutoML Pipeline Selection: Efficiently Navigating the Combinatorial Space
Cornell University; Keywords: AutoML; meta-learning; pipeline search; tensor decomposition;submodular optimization; experiment design; greedy algorithms

Bounded-Leakage Differential Privacy
UBC (Hebrew University of Jerusalem)

Conflict Forecasting and Prediction
Harvard/UTD; Keywords: conflict forecasting; predictive models; machine learning; international conflict; civil war; terrorism

Correlation Sketches for Approximate Join-Correlation Queries
NYU; Keywords: Dataset search; Correlation; Join-Correlation estimation; Sketching algorithms;

Feature Selection in Learning Using Privileged Information
Perspecta Labs , (formerly Vencore Labs)

Updated: 07 June 2021, 333 papers