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We start with an overview of a class of submodular functions called SCMMs (sums of concave composed with non-negative modular functions plus a final arbitrary modular).
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An analysis of approximations for maximizing submodular set functions— II
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An analysis of approximations for maximizing submodular set functions i
G.L. Nemhauser, L.A. Wolsey, and M.L. Fisher · 1978
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Minimizing a submodular function on a lattice
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Decomposition of submodular functions
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Graphical models
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A non-shannon-type conditional inequality of information quantities
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The multiinformation function as a tool for measuring stochastic dependence
Milan Studenỳ and Jirina Vejnarová · 1998
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Supermodularity and complementarity
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Minimizing a submodular function arising from a concave function
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Maximizing the spread of influence through a social network
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Discrete convex analysis
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Convex optimization
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Visual categorization with bags of keypoints
Gabriella Csurka, Christopher Dance, Lixin Fan, Jutta Willamowski, and Cédric Bray · 2004
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Algorithmic graph theory and perfect graphs
Martin Charles Golumbic · 2004
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What energy functions can be minimized via graph cuts?
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Introductory lectures on convex optimization: A basic course
Yurii Nesterov · 2004
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Submodular Functions and Optimization
S. Fujishige · 2005
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Unsupervised large-vocabulary word sense disambiguation with graph-based algorithms for sequence data labeling
R. Mihalcea · 2005
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A submodular-supermodular procedure with applications to discriminative structure learning
Mukund Narasimhan and Jeff Bilmes · 2005
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Q-clustering
Mukund Narasimhan, Nebojsa Jojic, and Jeff Bilmes · 2005
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Learning structured prediction models: A large margin approach
Ben Taskar, Vassil Chatalbashev, Daphne Koller, and Carlos Guestrin · 2005
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Convex functions and their applications: a contemporary approach
Constantin Niculescu and Lars-Erik Persson · 2006
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Methods of information geometry
Shun-ichi Amari and Hiroshi Nagaoka · 2007
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A visual bag of words method for interactive qualitative localization and mapping
David Filliat · 2007
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Computational geometric approach to submodular function minimization for multiclass queueing systems
Toshinari Itoko and Satoru Iwata · 2007
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Cost-effective outbreak detection in networks
Jure Leskovec, Andreas Krause, Carlos Guestrin, Christos Faloutsos, Jeanne VanBriesen, and Natalie Glance · 2007
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Graph connectivity measures for unsupervised word sense disambiguation
R. Navigli and M. Lapata · 2007
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Submodularity in combinatorial optimization
J. Vondrák · 2007
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Evaluating bag-of-visual-words representations in scene classification
Jun Yang, Yu-Gang Jiang, Alexander G Hauptmann, and Chong-Wah Ngo · 2007
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Bag-of-visual-words models for adult image classification and filtering
Thomas Deselaers, Lexi Pimenidis, and Hermann Ney · 2008
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Optimal marketing strategies over social networks
Jason Hartline, Vahab Mirrokni, and Mukund Sundararajan · 2008
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Robust submodular observation selection
Andreas Krause, Brendan McMahan, Carlos Guestrin, and Anupam Gupta · 2008
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Language modeling for bag-of-visual words image categorization
Pierre Tirilly, Vincent Claveau, and Patrick Gros · 2008
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Exploring syntactic structured features over parse trees for relation extraction using kernel methods
M. Zhang, G. Zhou, and A. Aw · 2008
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Graph-based learning for statistical machine translation
A. Alexandrescu and K. Kirchhoff · 2009
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Learning Deep Architectures for AI
Y. Bengio · 2009
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Optimal bounds on approximation of submodular and XOS functions by juntas
V. Feldman and J. Vondrák · 2013
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Representation, approximation and learning of submodular functions using low-rank decision trees
Vitaly Feldman, Pravesh Kothari, and Jan Vondrák · 2013
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Learning binary hash codes for large-scale image search
Kristen Grauman and Rob Fergus · 2013
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Towards minimizing k-submodular functions
Anna Huber and Vladimir Kolmogorov · 2013
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Fast semidifferential based submodular function optimization
R. Iyer, S. Jegelka, and J. Bilmes · 2013
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Fast approximate kNN graph construction for high dimensional data via recursive Lanczos bisection
J. Chen, H.-R. Fang, and Y. Saad · 2009
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Turning down the noise in the blogosphere
Khalid El-Arini, Gaurav Veda, Dafna Shahaf, and Carlos Guestrin · 2009
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Approximating submodular functions everywhere
M.X. Goemans, N.J.A. Harvey, S. Iwata, and V. Mirrokni · 2009
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Graph construction and b-matching for semi-supervised learning
T. Jebara, J. Wang, and S.-F. Chang · 2009
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Finding groups in data: an introduction to cluster analysis
Leonard Kaufman and Peter J Rousseeuw · 2009
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Submodular optimization with submodular cover and submodular knapsack constraints
Rishabh Iyer and Jeff Bilmes · 2013
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Fast semidifferential-based submodular function optimization
Rishabh Iyer, Stefanie Jegelka, and Jeff A. Bilmes · 2013
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Reflection methods for user-friendly submodular optimization
Stefanie Jegelka, Francis Bach, and Suvrit Sra · 2013
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Using n-gram and word network features for native language identification
S. Lahiri and R. Mihalcea · 2013
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A novel graph-based compact representation of word alignment
Q. Liu, Z. Tu, and S. Lin · 2013
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Submodular feature selection for high-dimensional acoustic score spaces
Yuzong Liu, Kai Wei, Katrin Kirchhoff, Yisong Song, and Jeff Bilmes · 2013
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Structural parse tree features for text representation
S. Massung, C. Zhai, and J. Hockenmaier · 2013
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
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Learning word embeddings efficiently with noise-contrastive estimation
Andriy Mnih and Koray Kavukcuoglu · 2013
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Explicit and implicit syntactic features for text classification
M. Post and S. Bergsma · 2013
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Graph propagation for paraphrasing out-of-vocabulary words in statistical machine translation
M. Razmara, M. Siahbani, G. Haffari, and A. Sarkar · 2013
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Convex Analysis for Minimizing and Learning Submodular Set Functions
Peter Stobbe · 2013
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Fast kNN graph construction with locality sensitive hashing
Y.-M. Zhang, K. Huang, G. Geng, and C.-L. Liu · 2013
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Notes on using Determinantal Point Processes for Clustering with Applications to Text Clustering
A. Agarwal, Choromanska A., and K. Choromanski · 2014
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Streaming submodular maximization: Massive data summarization on the fly
A. Badanidiyuru, B. Mirzasoleiman, A. Karbasi, and A. Krause · 2014
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Fast algorithms for maximizing submodular functions
Ashwinkumar Badanidiyuru and Jan Vondrák · 2014
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Discover feature engineering, how to engineer features and how to get good at it, 2014
Jason Brownlee · 2014
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Submodular maximization with cardinality constraints
Niv Buchbinder, Moran Feldman, Joseph Seffi Naor, and Roy Schwartz · 2014
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Submodular function maximization via the multilinear relaxation and contention resolution schemes
Chandra Chekuri, Jan Vondrák, and Rico Zenklusen · 2014
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Approximate Inference for Determinantal Point Processes
Jennifer Gillenwater · 2014
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A convolutional neural network for modelling sentences
Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom · 2014
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Submodularity for data selection in machine translation
K. Kirchhoff and J. Bilmes · 2014
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On the convergence rate of decomposable submodular function minimization
R. Nishihara, S Jegelka, and M. I. Jordan · 2014
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Max-Margin Tensor Neural Network for Chinese Word Segmentation
W. Pei · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning · 2014
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Unsupervised word sense disambiguation with n-gram features
D. Preotiuc-Pietro and F. Hristea · 2014
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A submodular optimization approach to sentence set selection
Yusuke Shinohara · 2014
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Learning mixtures of submodular functions for image collection summarization
S. Tschiatschek, R. Iyer, H. Wei, and J. Bilmes · 2014
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Unsupervised submodular subset selection for speech data
K. Wei, Y. Liu, K. Kirchhoff, and J. Bilmes · 2014
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Sentiment classification in under-resourced languages using graph-based semi-supervised learning methods
R. Yong, K. Nobuhiro, N. Yoshinaga, and M. Kitsuregawa · 2014
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The power of randomization: Distributed submodular maximization on massive datasets
Rafael Barbosa, Alina Ene, Huy L Nguyen, and Justin Ward · 2015
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Streaming algorithms for submodular function maximization
Chandra Chekuri, Shalmoli Gupta, and Kent Quanrud · 2015
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The power of depth for feedforward neural networks
Ronen Eldan and Ohad Shamir · 2015
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Submodular hamming metrics
Jennifer Gillenwater, Rishabh Iyer, Bethany Lusch, Rahul Kidambi, and Jeff Bilmes · 2015
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Sampling from probabilistic submodular models
Alkis Gotovos, S. Hamed Hassani, and Andreas Krause · 2015
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Submodular point processes
Rishabh Iyer and Jeff Bilmes · 2015
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Fast greedy algorithms in mapreduce and streaming
Ravi Kumar, Benjamin Moseley, Sergei Vassilvitskii, and Andrea Vattani · 2015
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Deep learning
Y. LeCun, Y. Bengio, and G. Hinton · 2015
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Representation learning using multi-task deep neural networks for semantic classification and information retrieval
Xiaodong Liu, Jianfeng Gao, Xiaodong He, Li Deng, Kevin Duh, and Ye-Yi Wang · 2015
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Distributed submodular cover: Succinctly summarizing massive data
Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, and Andreas Krause · 2015
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Bipartite matching generalizations for peptide identification in tandem mass spectrometry
Wenruo Bai, Jeffrey Bilmes, and William S. Noble · 2016
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A new framework for distributed submodular maximization
Rafael Da Ponte Barbosa, Alina Ene, Huy L Nguyen, and Justin Ward · 2016
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Deep submodular functions: Definitions & learning
Brian Dolhansky and Jeff Bilmes · 2016
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Deep submodular functions: Definitions and learning
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Deep learning
Ian Goodfellow, Yoshua Bengio, and Aaron Courville · 2016
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Submodular optimization under noise
Avinatan Hassidim and Yaron Singer · 2016
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Multi-agent and multivariate submodular optimization
Richard Santiago and F. Bruce Shepherd · 2016
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Feature engineering — wikipedia, the free encyclopedia, 2016
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Mastering Feature Engineering: Principles and Techniques for Data Scientists
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