Ruprecht-Karls-Universität Heidelberg

Publications

  1. J. Kreutzer, A. Sokolov. Learning to Segment Inputs for NMT Favors Character-Level Processing, Int. Workshop on Spoken Language Translation (IWSLT), 2018 [poster] [extended report]
  2. A. Sokolov, J. Hitschler, S. Riezler. Sparse Stochastic Zeroth-Order Optimization with an Application to Bandit Structured Prediction, 2018 [ArXiv]
  3. F. Hieber, T. Domhan, M. Denkowski, D. Vilar, A. Sokolov, A. Clifton, M. Post. Sockeye: A Toolkit for Neural Machine Translation, American Machine Translation Association (AMTA), 2018 [complete ArXiv version] [code]
  4. C. Lawrence, A. Sokolov, S. Riezler. Counterfactual Learning from Bandit Feedback under Deterministic Logging: A Case Study in Statistical Machine Translation, Empirical Methods in Natural Language Processing (EMNLP), Copenhagen, Denmark, 2017 [poster]
  5. A. Sokolov, J. Kreutzer, K. Sunderland, P. Danchenko, W. Szymaniak, H. Fürstenau, S. Riezler. A Shared Task on Bandit Learning for Machine Translation, Conference on Machine Translation (WMT), Copenhagen, Denmark, 2017 [task page] [slides]
  6. J. Kreutzer, A. Sokolov, S. Riezler. Bandit Structured Prediction for Neural Sequence-to-Sequence Learning, Association of Computational Linguistics (ACL), Vancouver, Canada, 2017 [poster]
  7. A. Sokolov, J. Kreutzer, C. Lo, S. Riezler. Stochastic Structured Prediction under Bandit Feedback, Neural Information Processing Systems (NIPS), Barcelona, Spain, 2016 [poster] [code] [video]
  8. A. Sokolov, J. Kreutzer, C. Lo, S. Riezler. Learning Structured Predictors from Bandit Feedback for Interactive NLP, Association of Computational Linguistics (ACL), Berlin, Germany, 2016 [slides] [code 1] [code 2]
  9. V. Boteva, D. Gholipour, A. Sokolov, S. Riezler. A Full-Text Learning to Rank Dataset for Medical Information Retrieval, European Conference on Information Retrieval (ECIR), Padova, Italy, 2016 [poster] [data] [bib]
  10. A. Sokolov, S. Riezler, T. Urvoy. Bandit Structured Prediction for Learning from Partial Feedback in Statistical Machine Translation, MT Summit, Miami, FL, USA, 2015 [slides]
  11. A. Sokolov, S. Riezler, S. B. Cohen. A Coactive Learning View of Online Structured Prediction in Statistical Machine Translation. In Proc. of the Conference of Computational Natural Language Learning (CoNLL), Beijing, China, 2015. [slides]
  12. A. Sokolov, S. Riezler, S. B. Cohen. Coactive Learning for Interactive Machine Translation. In Proc. of the ICML Workshop on Machine Learning for Interactive Systems (ICML-MLIS), Lille, France, 2015.
  13. A. Sokolov, F. Hieber, S. Riezler. Learning to Translate Queries for CLIR. In Proc. of the ACM SIGIR Conference (SIGIR), Gold Coast, Australia, 2014. [poster]
  14. S. Schamoni, F. Hieber, A. Sokolov, S. Riezler. Learning Translational and Knowledge-based Similarities from Relevance Rankings for Cross-Language Retrieval. In Proc. of the Association for Computational Linguistics (ACL), 2014. [poster] [data] [bib]
  15. A. Sokolov, G. Wisniewski, F. Yvon. Lattice BLEU Oracles for Machine Translation. Transactions on Speech and Language Processing (TSLP), ACM, 10(4)18:1-18:29, 2014. [publisher]
  16. A. Sokolov, S. Riezler. Task-driven Greedy Learning of Feature Hashing Functions. In Proc. of the NIPS Workshop "Big Learning : Advances in Algorithms and Data Management" (NIPS-BigLearn), Lake Tahoe, USA, 2013. [poster]
  17. A. Sokolov, L. Jehl, F. Hieber, S. Riezler. Boosting Cross-Language Retrieval by Learning Bilingual Phrase Associations from Relevance Rankings. In Proc. of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Seattle, USA, 2013 [slides] [data] [bibtex].
  18. P. Simianer, G. Stupperich, L. Jehl, K. Waeschle, A. Sokolov, S. Riezler. The HDU Discriminative SMT System for Constrained Data PatentMT at NTCIR10. In Proc. of the NTCIR Workshop (NTCIR), Tokyo, Japan, 2013 [poster]
  19. A. Sokolov, G. Wisniewski, F. Yvon. Non-linear n-best List Reranking with Few Features. In Proc. of the Association for Machine Translation in the Americas (AMTA), San Diego, USA, 2012. [slides] [another slides]
  20. M. Apidianaki, G. Wisniewski, A. Sokolov, A. Max, F. Yvon. WSD for n-best reranking and local language modeling in SMT. In Proc. of the ACL Workshop on Syntax, Semantics and Structure in Statistical Translation (ACL-SSST), Jeju, South Korea, 2012. [slides]
  21. A. Sokolov. Learning Semantic Similarity by Selecting Random Word Subsets. In Proc. of the NAACL Int. Workshop on Semantic Evaluation (SemEval-2012), in conjunction with the Joint Conference on Lexical and Computational Semantics (NAACL-SemEval/*SEM), Montreal, Canada, 2012. [poster]
  22. H.-S. Le, T. Lavergne, A. Allauzen, M. Apidianaki, L. Gong, A. Max, A. Sokolov, G. Wisniewski, F. Yvon, LIMSI@WMT12. In Proc. of the Workshop on Statistical Machine Translation (WMT), 2012. [poster]
  23. A. Sokolov, G. Wisniewski and F. Yvon. Computing Lattice BLEU Oracle Scores for Machine Translation. In Proc. of the Conference of the European Chapter of the Association for Computational Linguistics (EACL), Avignon, France, 2012. [slides]
  24. A. Sokolov, T. Urvoy, H.-S. Le. Low-Dimensional Feature Learning with Kernel Construction, In Proc. of the NIPS Workshop on Deep Learning and Unsupervised Feature Learning (NIPS-DL&UFL), Granada, Spain, 2011. 2nd & 3rd places in the Semi-Supervised Feature Learning Challenge [poster] [spotlight slides]
  25. K. Boudahmane, B. Buschbeck, E. Cho, J. M. Crego, M. Freitag, T. Lavergne, H. Ney, J. Niehues, S. Peitz, J. Senellart, A. Sokolov, A. Waibel, T. Wandmacher, J. Wuebker, F. Yvon. Advances on Spoken Language Translation in the Quaero Program, In Proc. of the International Workshop on Spoken Language Translation (IWSLT), San Francisco, USA, 2011. [slides]
  26. A. Allauzen, H. Bonneau-Maynard, H.-S. Le, A. Max, G. Wisniewski, F. Yvon, G. Adda, J. M. Crego, A. Lardilleux, T. Lavergne, and A. Sokolov. LIMSI@WMT11. In Proc. of the Workshop on Statistical Machine Translation (WMT), Edinburgh, UK, 2011. [poster]
  27. A. Sokolov and F. Yvon. Minimum error rate training semiring. In Proc. of the European Association for Machine Translation (EAMT), pages 241-248, Leuven, Belgium, 2011. [slides]
  28. A. Sokolov, T. Urvoy, L. Denoyer, and O. Ricard. MADSPAM consortium at the ECML/PKDD Discovery Challenge 2010. In Proc. of the Discovery Challenge Workshop of European Conference on Machine Learning (ECML/PKDD-Discovery), Barcelona, Spain, 2010. ECML/PKDD Discovery Challenge: 1st place at the English quality task & 2nd place @ general task. [slides]
  29. A. Sokolov. Methods of Neural Distributed Representation and Search for Similar Symbol Sequences in Classification Tasks Using Case-Based Reasoning. PhD thesis, 159 pages, Kyiv, Ukraine, April 2009. (in russian). [slides in english] [resume in ukrainian] [full pdf in russian] [slides in russian]
  30. A. Sokolov. Investigation of accelerated search for close text sequences with the help of vector representations. Journal of Cybernetics and System Analysis, 44(4):493-506. Springer, 2008. (translated). [pdf in russian]
  31. A. Sokolov. Randomized edit distance embedding in gene finding and intrusion detection. Journal of System Technologies, (2):126-139. 2008. (in russian). [pdf in russian]
  32. A. Sokolov. Vector representations for efficient comparison and search for similar strings. Journal of Cybernetics and System Analysis, 43(4):484-498. Springer, 2007. (translated). [pdf in russian]
  33. A. Sokolov. Searching for nearest strings with neural-like string embeddings. Journal of Information Theories and Applications, 14(3):294-299. 2007.
  34. A. Sokolov. Nearest string by neural-like encoding. In Proc. of 12th Int. Conf. Knowledge-Dialogue-Solution (KDS), pages 101-106, Varna, Bulgaria, 2006.
  35. A. Sokolov and D. Rachkovskij. Approaches to sequence similarity representation. Journal of Information Theories and Applications, 13(3):272-278. 2005.
  36. A. Sokolov and D. Rachkovskij. Some approaches to distributed encoding of sequences. In Proc. of 11th Int. Conf. Knowledge-Dialogue-Solution (KDS), volume 2, pages 522-528, Varna, Bulgaria, 2005.
  37. I. Misuno, D. Rachkovskij, S. Slipchenko, and A. Sokolov. Searching for text information with vector representations. Journal of Problems in Programming, pages 50-59. 2005. (in russian). [pdf in russian]
  38. I. Misuno, D. Rachkovskij, S. Slipchenko, and A. Sokolov. Processing text information with vector representations. In Proc. of the Int. Workshop on Inductive Modeling, pages 230-236, Kyiv, Ukraine, 2005. (in russian).
  39. I. Misuno, D. Rachkovskij, O. Revunova, S. Slipchenko, A. Sokolov, and O. Teteriuk. Modular software neurocomputer SNC: implementation and applications. Journal of Control Systems and Machines, (2):74-85. 2005. (in russian). [pdf in russian]
  40. A. Sokolov. Modern models for anomaly detection in computer systems. Journal of Control Systems and Machines, (5):67-73. 2004. (in ukrainian). [pdf in ukrainian] [pdf in russian]
  41. V. Grytsenko, I. Misuno, D. Rachkovskij, O. Revunova, S. Slipchenko, and A. Sokolov. Concept and architecture of the software neurocomputer SNC. Journal of Control Systems and Machines, (3):3-14. 2004. (in russian). [pdf in russian]
  42. N. Kussul and A. Sokolov. Adaptive Anomaly Detection in the Behavior of Computer Systems Users on the Basis of Markov Chains of Variable Order. Part II. Anomaly Detection Methods and Experimental Results. Journal of Automation and Information Sciences, 35(8):1c-5c. Begell House, 2003. (translated). [pdf in russian]
  43. N. Kussul and A. Sokolov. Adaptive Anomaly Detection of Computer System User's Behavior Applying Markovian Chains with Variable Memory Length. Part I. Adaptive Model of Markovian Chains with Variable Memory Length. Journal of Automation and Information Sciences, 35(6):1a-9a. Begell House, 2003. (translated). [pdf in russian]
  44. A. Sokolov and D. Rachkovskij. On handling replay attacks in intrusion detection systems. Journal of Information Theories and Applications, 10(3):341-348. 2003.
  45. A. Sokolov. An adaptive detection of anomalies in user's behavior. In Proc. of the Int. Joint Conf. on Neural Networks (IJCNN), volume 4, pages 2443-2447, Portland, Oregon, USA, 2003.
  46. A. Sokolov. Detecting anomalies with markov chains with variable memory length. Artificial Intelligence, (4):74-83. 2002. (in russian). [pdf in russian]
  47. I. Misuno, D. Rachkovskij, E. Revunova, and A. Sokolov. SNC: The software neurocomputer with modular architecture. In Proc. of the Int. Conf. "Problems of Neurocybernetics", volume 2, pages 109-113, Rostov-on-Don, Russia, 2002.
  48. O. Reznik, N. Kussul, and A. Sokolov. Detecting anomalous user activity in computer systems using neural-network prediction. In Proc. of the Int. Conf. on Prediction and Decision Making under Uncertainties, pages 116-117, Kyiv, Ukraine, 2001. (in ukrainian).
  49. A. Reznik, N. Kussul, and A. Sokolov. Identification of user activity using neural networks. Journal of Cybernetics and Computer Science, 123:70-79. 1999. (in russian). [pdf in russian]
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