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

AlphaD3M: An Open-Source AutoML Library for Multiple ML Tasks Roque Lopez, Raoni Lourenco, Remi Rampin, Sonia Castelo, Aécio SR Santos, Jorge Henrique Piazentin Ono, Claudio Silva, Juliana Freire AutoML Conference 2023, 2023

Using Pipeline Performance Prediction to Accelerate AutoML Systems Haoxiang Zhang, Roque López, Aécio Santos, Jorge Piazentin Ono, Aline Bessa, Juliana Freire Proceedings of the Seventh Workshop on Data Management for End-to-End Machine Learning, 2023 Best paper award.

An ecosystem of applications for modeling political Aline Bessa, Sonia Castelo, Rémi Rampin, Aécio Santos, Mike Shoemate, Vito D'Orazio, Juliana Freire Proceedings of the 2021 International Conference on Management of Data

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