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Expectation-Maximization for Learning Determinantal Point Processes

Expectation-Maximization for Learning Determinantal Point Processes

4 November 2014
Jennifer Gillenwater
Alex Kulesza
E. Fox
B. Taskar
ArXiv (abs)PDFHTML

Papers citing "Expectation-Maximization for Learning Determinantal Point Processes"

30 / 30 papers shown
Title
A Family of Distributions of Random Subsets for Controlling Positive and Negative Dependence
A Family of Distributions of Random Subsets for Controlling Positive and Negative Dependence
Sangwoo Shin
H. Hino
85
0
0
02 Aug 2024
Enhancing Neural Subset Selection: Integrating Background Information
  into Set Representations
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations
Binghui Xie
Yatao Bian
Kaiwen Zhou
Yongqiang Chen
Peilin Zhao
Bo Han
Wei Meng
James Cheng
59
1
0
05 Feb 2024
Graph Convolutional Neural Networks with Diverse Negative Samples via
  Decomposed Determinant Point Processes
Graph Convolutional Neural Networks with Diverse Negative Samples via Decomposed Determinant Point Processes
Wei Duan
Junyu Xuan
Maoying Qiao
Jie Lu
84
11
0
05 Dec 2022
Concrete Score Matching: Generalized Score Matching for Discrete Data
Concrete Score Matching: Generalized Score Matching for Discrete Data
Chenlin Meng
Kristy Choi
Jiaming Song
Stefano Ermon
DiffM
262
71
0
02 Nov 2022
Neural Estimation of Submodular Functions with Applications to
  Differentiable Subset Selection
Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection
A. De
Soumen Chakrabarti
96
5
0
20 Oct 2022
Explicit and Implicit Pattern Relation Analysis for Discovering
  Actionable Negative Sequences
Explicit and Implicit Pattern Relation Analysis for Discovering Actionable Negative Sequences
Wei Wang
LongBing Cao
33
1
0
04 Apr 2022
Learning Neural Set Functions Under the Optimal Subset Oracle
Learning Neural Set Functions Under the Optimal Subset Oracle
Zijing Ou
Tingyang Xu
Qinliang Su
Yingzhen Li
P. Zhao
Yatao Bian
BDL
52
10
0
03 Mar 2022
Scalable Sampling for Nonsymmetric Determinantal Point Processes
Scalable Sampling for Nonsymmetric Determinantal Point Processes
Insu Han
Mike Gartrell
Jennifer Gillenwater
Elvis Dohmatob
Amin Karbasi
61
4
0
20 Jan 2022
Deep Time Series Forecasting with Shape and Temporal Criteria
Deep Time Series Forecasting with Shape and Temporal Criteria
Vincent Le Guen
Nicolas Thome
AI4TS
75
30
0
09 Apr 2021
Wasserstein Learning of Determinantal Point Processes
Wasserstein Learning of Determinantal Point Processes
Lucas Anquetil
Mike Gartrell
A. Rakotomamonjy
Ugo Tanielian
Clément Calauzènes
17
2
0
19 Nov 2020
Probabilistic Time Series Forecasting with Structured Shape and Temporal
  Diversity
Probabilistic Time Series Forecasting with Structured Shape and Temporal Diversity
Vincent Le Guen
Nicolas Thome
AI4TS
87
27
0
14 Oct 2020
Testing Determinantal Point Processes
Testing Determinantal Point Processes
Khashayar Gatmiry
Maryam Aliakbarpour
Stefanie Jegelka
69
1
0
09 Aug 2020
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point
  Processes
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Mike Gartrell
Insu Han
Elvis Dohmatob
Jennifer Gillenwater
Victor-Emmanuel Brunel
60
16
0
17 Jun 2020
DLow: Diversifying Latent Flows for Diverse Human Motion Prediction
DLow: Diversifying Latent Flows for Diverse Human Motion Prediction
Ye Yuan
Kris Kitani
DiffM
124
243
0
18 Mar 2020
PTP: Parallelized Tracking and Prediction with Graph Neural Networks and
  Diversity Sampling
PTP: Parallelized Tracking and Prediction with Graph Neural Networks and Diversity Sampling
Xinshuo Weng
Ye Yuan
Kris Kitani
67
33
0
17 Mar 2020
Provable Non-Convex Optimization and Algorithm Validation via
  Submodularity
Provable Non-Convex Optimization and Algorithm Validation via Submodularity
Yatao Bian
46
3
0
18 Dec 2019
Diverse Trajectory Forecasting with Determinantal Point Processes
Diverse Trajectory Forecasting with Determinantal Point Processes
Ye Yuan
Kris Kitani
53
134
0
11 Jul 2019
Learning Nonsymmetric Determinantal Point Processes
Learning Nonsymmetric Determinantal Point Processes
Mike Gartrell
Victor-Emmanuel Brunel
Elvis Dohmatob
Syrine Krichene
51
43
0
30 May 2019
Diversified Hidden Markov Models for Sequential Labeling
Diversified Hidden Markov Models for Sequential Labeling
Maoying Qiao
Wei Bian
R. Xu
Dacheng Tao
13
11
0
05 Apr 2019
Learning Signed Determinantal Point Processes through the Principal
  Minor Assignment Problem
Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem
Victor-Emmanuel Brunel
152
28
0
01 Nov 2018
A Polynomial Time MCMC Method for Sampling from Continuous DPPs
A Polynomial Time MCMC Method for Sampling from Continuous DPPs
S. Gharan
A. Rezaei
51
4
0
20 Oct 2018
Diversity in Machine Learning
Diversity in Machine Learning
Z. Gong
P. Zhong
Weidong Hu
55
203
0
04 Jul 2018
Differentiable Submodular Maximization
Differentiable Submodular Maximization
Sebastian Tschiatschek
Aytunc Sahin
Andreas Krause
68
45
0
05 Mar 2018
Learning Determinantal Point Processes by Corrective Negative Sampling
Learning Determinantal Point Processes by Corrective Negative Sampling
Zelda E. Mariet
Mike Gartrell
S. Sra
63
3
0
15 Feb 2018
Query-Focused Video Summarization: Dataset, Evaluation, and A Memory
  Network Based Approach
Query-Focused Video Summarization: Dataset, Evaluation, and A Memory Network Based Approach
Aidean Sharghi
Jacob S. Laurel
Boqing Gong
EgoV
122
137
0
16 Jul 2017
Rates of estimation for determinantal point processes
Rates of estimation for determinantal point processes
Victor-Emmanuel Brunel
Ankur Moitra
Philippe Rigollet
John C. Urschel
83
16
0
03 Jun 2017
Learning Determinantal Point Processes in Sublinear Time
Learning Determinantal Point Processes in Sublinear Time
Christophe Dupuy
Francis R. Bach
78
26
0
19 Oct 2016
Low-Rank Factorization of Determinantal Point Processes for
  Recommendation
Low-Rank Factorization of Determinantal Point Processes for Recommendation
Mike Gartrell
Ulrich Paquet
Noam Koenigstein
79
77
0
17 Feb 2016
Efficient Sampling for k-Determinantal Point Processes
Efficient Sampling for k-Determinantal Point Processes
Chengtao Li
Stefanie Jegelka
S. Sra
139
52
0
04 Sep 2015
Fixed-point algorithms for learning determinantal point processes
Fixed-point algorithms for learning determinantal point processes
Zelda E. Mariet
S. Sra
104
53
0
04 Aug 2015
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