D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 30 Citations 4,285 123 World Ranking 6912 National Ranking 288

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

His primary areas of study are Artificial intelligence, Regional science, Recommender system, Collaborative filtering and Operations research. His Artificial intelligence study frequently draws parallels with other fields, such as Machine learning. His Machine learning research is multidisciplinary, incorporating perspectives in Latent Dirichlet allocation, Aggregate, Information retrieval and Bayesian probability.

His work on MovieLens as part of general Recommender system study is frequently linked to Matrix decomposition, therefore connecting diverse disciplines of science. His work on Cold start as part of his general Collaborative filtering study is frequently connected to Predictive power and Task, thereby bridging the divide between different branches of science. Scott Sanner combines subjects such as Applications of artificial intelligence and Music and artificial intelligence with his study of Operations research.

His most cited work include:

  • AutoRec: Autoencoders Meet Collaborative Filtering (495 citations)
  • Improving LDA topic models for microblogs via tweet pooling and automatic labeling (293 citations)
  • Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity (94 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Artificial intelligence, Mathematical optimization, Machine learning, Markov decision process and Dynamic programming. Scott Sanner has included themes like Collaborative filtering and Information retrieval in his Artificial intelligence study. The Bellman equation and Linear programming research Scott Sanner does as part of his general Mathematical optimization study is frequently linked to other disciplines of science, such as Influence diagram and Piecewise linear function, therefore creating a link between diverse domains of science.

Scott Sanner has researched Machine learning in several fields, including Class and Bayesian probability. His research on Markov decision process also deals with topics like

  • Probabilistic logic that intertwine with fields like Domain,
  • Set together with Relevance. His Dynamic programming research is multidisciplinary, incorporating elements of Nonlinear programming and State.

He most often published in these fields:

  • Artificial intelligence (33.33%)
  • Mathematical optimization (31.61%)
  • Machine learning (21.26%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (33.33%)
  • Machine learning (21.26%)
  • Task (8.62%)

In recent papers he was focusing on the following fields of study:

Scott Sanner mainly focuses on Artificial intelligence, Machine learning, Task, Deep learning and Artificial neural network. His Artificial intelligence study integrates concerns from other disciplines, such as Collaborative filtering and Recommender system. His studies in Machine learning integrate themes in fields like Class, State, Class, Mixture model and Data stream.

His work deals with themes such as Linear programming, Mathematical optimization, Set and Overhead, which intersect with Artificial neural network. His Mathematical optimization study combines topics in areas such as Bayesian inference and Nonlinear system. His Autoencoder research includes themes of Social media, Similarity and Data science.

Between 2018 and 2021, his most popular works were:

  • Deep Learning with Microfluidics for Biotechnology. (62 citations)
  • Comparison of machine learning models for occupancy prediction in residential buildings using connected thermostat data (21 citations)
  • Noise Contrastive Estimation for One-Class Collaborative Filtering (13 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

Scott Sanner spends much of his time researching Artificial intelligence, Deep learning, Artificial neural network, Recommender system and Constraint. The Artificial intelligence study combines topics in areas such as Machine learning, Key and Collaborative filtering. His work on Classifier as part of general Machine learning research is often related to Contextual image classification, thus linking different fields of science.

The study incorporates disciplines such as Stability, Continual learning and Software engineering in addition to Deep learning. Many of his research projects under Artificial neural network are closely connected to Graphics, Lab-on-a-chip and Biotechnology with Graphics, Lab-on-a-chip and Biotechnology, tying the diverse disciplines of science together. Information retrieval covers he research in Recommender system.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

AutoRec: Autoencoders Meet Collaborative Filtering

Suvash Sedhain;Aditya Krishna Menon;Scott Sanner;Lexing Xie.
the web conference (2015)

663 Citations

Improving LDA topic models for microblogs via tweet pooling and automatic labeling

Rishabh Mehrotra;Scott Sanner;Wray Buntine;Lexing Xie.
international acm sigir conference on research and development in information retrieval (2013)

442 Citations

Towards object mapping in non-stationary environments with mobile robots

R. Biswas;B. Limketkai;S. Sanner;S. Thrun.
intelligent robots and systems (2002)

188 Citations

The 2014 International Planning Competition: Progress and Trends

Mauro Vallati;Lukás Chrpa;Marek Grzes;Thomas Leo McCluskey.
Ai Magazine (2015)

127 Citations

A Survey of the Seventh International Planning Competition

Amanda Coles;Andrew Coles;Angel García Olaya;Sergio Jiménez.
Ai Magazine (2012)

126 Citations

Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity

Marian-Andrei Rizoiu;Lexing Xie;Scott Sanner;Manuel Cebrian.
the web conference (2017)

114 Citations

Practical solution techniques for first-order MDPs

Scott Sanner;Craig Boutilier.
Artificial Intelligence (2009)

112 Citations

Algorithms for Direct 01 Loss Optimization in Binary Classification

Tan Nguyen;Scott Sanner.
international conference on machine learning (2013)

109 Citations

Social collaborative filtering for cold-start recommendations

Suvash Sedhain;Scott Sanner;Darius Braziunas;Lexing Xie.
conference on recommender systems (2014)

109 Citations

Affine algebraic decision diagrams (AADDs) and their application to structured probabilistic inference

Scott Sanner;David McAllester.
international joint conference on artificial intelligence (2005)

108 Citations

Best Scientists Citing Scott Sanner

Kristian Kersting

Kristian Kersting

TU Darmstadt

Publications: 26

Lexing Xie

Lexing Xie

Australian National University

Publications: 23

Christian Lebiere

Christian Lebiere

Carnegie Mellon University

Publications: 19

Luc De Raedt

Luc De Raedt

KU Leuven

Publications: 16

Xueqi Cheng

Xueqi Cheng

Chinese Academy of Sciences

Publications: 13

Maarten de Rijke

Maarten de Rijke

University of Amsterdam

Publications: 13

Xindong Wu

Xindong Wu

Hefei University of Technology

Publications: 13

James Caverlee

James Caverlee

Texas A&M University

Publications: 12

Leslie Pack Kaelbling

Leslie Pack Kaelbling

MIT

Publications: 12

Wray Buntine

Wray Buntine

Monash University

Publications: 12

Lina Yao

Lina Yao

UNSW Sydney

Publications: 11

Alexander Tuzhilin

Alexander Tuzhilin

New York University

Publications: 10

Philip S. Yu

Philip S. Yu

University of Illinois at Chicago

Publications: 10

Xiangnan He

Xiangnan He

University of Science and Technology of China

Publications: 10

Xin Luo

Xin Luo

Chinese Academy of Sciences

Publications: 9

Jun Xu

Jun Xu

Renmin University of China

Publications: 9

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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