Fetching the paper…
Reading the bibliography…
We propose in this paper a differentiable learning loss between time series, building upon the celebrated dynamic time warping (DTW) discrepancy.
Les éléments aléatoires de nature quelconque dans un espace distancié
Fréchet, Maurice · 1948
Earlier work this paper cites.
On the theory of dynamic programming
Bellman, Richard · 1952
Earlier work this paper cites.
A dynamic programming approach to continuous speech recognition
Sakoe, Hiroaki and Chiba, Seibi · 1971
Earlier work this paper cites.
Decoding for channels with insertions, deletions, and substitutions with applications to speech recognition
Bahl, L and Jelinek, Frederick · 1975
Earlier work this paper cites.
Dynamic programming algorithm optimization for spoken word recognition
Sakoe, Hiroaki and Chiba, Seibi · 1978
Earlier work this paper cites.
Least squares quantization in pcm
Lloyd, Stuart · 1982
Earlier work this paper cites.
Learning string-edit distance
Ristad, Eric Sven and Yianilos, Peter N · 1998
Earlier work this paper cites.
Efficient retrieval of similar time sequences under time warping
Yi, Byoung-Kee, Jagadish, HV, and Faloutsos, Christos · 1998
Earlier work this paper cites.
Multi-step-ahead prediction using dynamic recurrent neural networks
Parlos, Alexander G, Rais, Omar T, and Atiya, Amir F · 2000
Earlier work this paper cites.
The Elements of Statistical Learning
Hastie, Trevor, Tibshirani, Robert, and Friedman, Jerome · 2001
Earlier work this paper cites.
Diagnosis of multiple cancer types by shrunken centroids of gene expression
Tibshirani, Robert, Hastie, Trevor, Narasimhan, Balasubramanian, and Chu, Gilbert · 2002
Cited alongside, same era.
Convex Optimization
Boyd, Stephen and Vandenberghe, Lieven · 2004
Cited alongside, same era.
Protein homology detection using string alignment kernels
Saigo, Hiroto, Vert, Jean-Philippe, Ueda, Nobuhisa, and Akutsu, Tatsuya · 2004
Cited alongside, same era.
New introduction to multiple time series analysis
Lütkepohl, Helmut · 2005
Cited alongside, same era.
Optimizing amino acid substitution matrices with a local alignment kernel
Saigo, Hiroto, Vert, Jean-Philippe, and Akutsu, Tatsuya · 2006
Cited alongside, same era.
Predicting Structured Data
Bakir, GH, Hofmann, T, Schölkopf, B, Smola, AJ, Taskar, B, and Vishwanathan, SVN · 2007
Cited alongside, same era.
Summarizing a set of time series by averaging: From steiner sequence to compact multiple alignment
Petitjean, François and Gançarski, Pierre · 2012
Later among the works it cites.
Fast computation of Wasserstein barycenters
Cuturi, Marco and Doucet, Arnaud · 2014
Later among the works it cites.
Metric learning for temporal sequence alignment
Garreau, Damien, Lajugie, Rémi, Arlot, Sylvain, and Bach, Francis · 2014
Later among the works it cites.
Adam: A method for stochastic optimization
Kingma, Diederik and Ba, Jimmy · 2014
Later among the works it cites.
Dynamic time warping averaging of time series allows faster and more accurate classification
Petitjean, François, Forestier, Germain, Webb, Geoffrey I, Nicholson, Ann E, Chen, Yanping, and Keogh, Eamonn · 2014
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
A kernel for time series based on global alignments
Cuturi, Marco, Vert, Jean-Philippe, Birkenes, Oystein, and Matsui, Tomoko · 2007
Cited alongside, same era.
Linear and integer programming vs linear integration and counting: a duality viewpoint
Lasserre, Jean B · 2009
Cited alongside, same era.
Fast global alignment kernels
Cuturi, Marco · 2011
Cited alongside, same era.
A global averaging method for dynamic time warping, with applications to clustering
Petitjean, François, Ketterlin, Alain, and Gançarski, Pierre · 2011
Cited alongside, same era.
Chen, Yanping, Keogh, Eamonn, Hu, Bing, Begum, Nurjahan, Bagnall, Anthony, Mueen, Abdullah, and Batista, Gustavo · 2015
Later among the works it cites.
Learning with a Wasserstein loss
Zhang, C., Frogner, C., Mobahi, H., Araya-Polo, M., and Poggio, T · 2015
Later among the works it cites.
Higher-order factorization machines
Blondel, Mathieu, Fujino, Akinori, Ueda, Naonori, and Ishihata, Masakazu · 2016
Later among the works it cites.
Fast dictionary learning with a smoothed Wasserstein loss
Rolet, A., Cuturi, M., and Peyré, G · 2016
Later among the works it cites.
Nonsmooth analysis and subgradient methods for averaging in dynamic time warping spaces
Schultz, David and Jain, Brijnesh · 2017
Closest in time.