Ruprecht-Karls-Universität Heidelberg

Publications

  1. I. Bejan, A. Sokolov, K. Filippova. Make Every Example Count: On the Stability and Utility of Self-Influence for Learning from Noisy NLP Datasets, Empirical Methods in Natural Language Processing (EMNLP), 2023 [ArXiv]
  2. R. Hubert, A. Sokolov, S. Riezler. Improving End-to-End Speech Translation by Imitation-Based Knowledge Distillation with Synthetic Transcripts, Int. Workshop on Spoken Language Translation (IWSLT), 2023
  3. A. Schioppa, P. Zablotskaia, D. Vilar, A. Sokolov. Scaling Up Influence Functions, Association for the Advancement of Artificial Intelligence (AAAI), 2022, [poster]
  4. J. Kreutzer, D. Vilar, A. Sokolov. Bandits Don't Follow Rules: Balancing Multi-Facet Machine Translation with Multi-Armed Bandits, Empirical Methods in Natural Language Processing (EMNLP), 2021
  5. A. Schioppa, A. Sokolov, D. Vilar, K. Filippova. Controlling Machine Translation for Multiple Attributes with Additive Interventions, Empirical Methods in Natural Language Processing (EMNLP), 2021, [poster]
  6. N. Berger, S. Riezler, A. Sokolov, S. Ebert. Don't Search for a Search Method - Simple Heuristics Suffice for Adversarial Text Attacks, Empirical Methods in Natural Language Processing (EMNLP), 2021
  7. L. Hormann, A. Sokolov. Fixing exposure bias with imitation learning needs powerful oracles, 2021, [ArXiv]
  8. I. Caswell, J. Kreutzer, L. Wang, A. Wahab, D. van Esch, N. Ulzii-Orshikh, A. Tapo, N. Subramani, A. Sokolov, C. Sikasote, M. Setyawan, S. Sarin, S. Samb, B. Sagot, C. Rivera, A. Rios, I. Papadimitriou, S. Osei, P. J. O. Suárez, I. Orife, K. Ogueji, R. A. Niyongabo, T. Q. Nguyen, M. Müller, A. Müller, S. H. Muhammad, N. Muhammad, A. Mnyakeni, J. Mirzakhalov, T. Matangira, C. Leong, N. Lawson, S. Kudugunta, Y. Jernite, M. Jenny, O. Firat, B. F. P. Dossou, S. Dlamini, N. de Silva, S. Ç. Ballı, S. Biderman, A. Battisti, A. Baruwa, A. Bapna, P. Baljekar, I. A. Azime, A. Awokoya, D. Ataman, O. Ahia, O. Ahia, S. Agrawal, M. Adeyemi. Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets, Transactions of the Association for Computational Linguistics (TACL), 2021, [ArXiv], [publisher]
  9. M. Ohta, N. Berger, A. Sokolov, S. Riezler. Sparse Perturbations for Improved Convergence in Stochastic Zeroth-Order Optimization, Learning, Optimization and Data Science (LOD), [ArXiv], 2020
  10. 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]
  11. A. Sokolov, J. Hitschler, S. Riezler. Sparse Stochastic Zeroth-Order Optimization with an Application to Bandit Structured Prediction, 2018 [ArXiv]
  12. 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]
  13. 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), 2017 [poster]
  14. 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), 2017 [task] [slides]
  15. J. Kreutzer, A. Sokolov, S. Riezler. Bandit Structured Prediction for Neural Sequence-to-Sequence Learning, Association of Computational Linguistics (ACL), 2017 [poster]
  16. A. Sokolov, J. Kreutzer, C. Lo, S. Riezler. Stochastic Structured Prediction under Bandit Feedback, Neural Information Processing Systems (NIPS), 2016 [poster] [code] [video]
  17. 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]
  18. 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), 2016 [poster] [data] [bib]
  19. A. Sokolov, S. Riezler, T. Urvoy. Bandit Structured Prediction for Learning from Partial Feedback in Statistical Machine Translation, Machine Translation Summit (MT Summit), 2015 [slides]
  20. A. Sokolov, S. Riezler, S. B. Cohen. A Coactive Learning View of Online Structured Prediction in Statistical Machine Translation. Computational Natural Language Learning (CoNLL), 2015. [slides]
  21. A. Sokolov, S. Riezler, S. B. Cohen. Coactive Learning for Interactive Machine Translation. ICML Workshop on Machine Learning for Interactive Systems (MLIS@ICML), 2015.
  22. A. Sokolov, F. Hieber, S. Riezler. Learning to Translate Queries for CLIR. ACM SIGIR Conference (SIGIR), 2014. [poster]
  23. S. Schamoni, F. Hieber, A. Sokolov, S. Riezler. Learning Translational and Knowledge-based Similarities from Relevance Rankings for Cross-Language Retrieval. Association for Computational Linguistics (ACL), 2014. [poster] [data] [bib]
  24. 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]
  25. A. Sokolov, S. Riezler. Task-driven Greedy Learning of Feature Hashing Functions. NIPS Workshop "Big Learning : Advances in Algorithms and Data Management" (NIPS-BigLearn), 2013. [poster]
  26. A. Sokolov, L. Jehl, F. Hieber, S. Riezler. Boosting Cross-Language Retrieval by Learning Bilingual Phrase Associations from Relevance Rankings. Empirical Methods in Natural Language Processing (EMNLP), 2013 [slides] [data] [bibtex].
  27. P. Simianer, G. Stupperich, L. Jehl, K. Waeschle, A. Sokolov, S. Riezler. The HDU Discriminative SMT System for Constrained Data PatentMT at NTCIR10. NTCIR Workshop (NTCIR), 2013 [poster]
  28. A. Sokolov, G. Wisniewski, F. Yvon. Non-linear n-best List Reranking with Few Features. Association for Machine Translation in the Americas (AMTA), San Diego, USA, 2012. [slides] [another slides]
  29. M. Apidianaki, G. Wisniewski, A. Sokolov, A. Max, F. Yvon. WSD for n-best reranking and local language modeling in SMT. ACL Workshop on Syntax, Semantics and Structure in Statistical Translation (ACL-SSST), 2012. [slides]
  30. A. Sokolov. Learning Semantic Similarity by Selecting Random Word Subsets. NAACL Workshop on Semantic Evaluation (NAACL-SemEval/*SEM), 2012. [poster]
  31. H.-S. Le, T. Lavergne, A. Allauzen, M. Apidianaki, L. Gong, A. Max, A. Sokolov, G. Wisniewski, F. Yvon, LIMSI@WMT12. Workshop on Statistical Machine Translation (WMT), 2012. [poster]
  32. A. Sokolov, G. Wisniewski and F. Yvon. Computing Lattice BLEU Oracle Scores for Machine Translation. European Chapter of the Association for Computational Linguistics (EACL), 2012. [slides]
  33. A. Sokolov, T. Urvoy, H.-S. Le. Low-Dimensional Feature Learning with Kernel Construction, NIPS Workshop on Deep Learning and Unsupervised Feature Learning (DL&UFL@NIPS), Granada, Spain, 2011. 2nd & 3rd places in the Semi-Supervised Feature Learning Challenge [poster] [spotlight slides]
  34. 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, International Workshop on Spoken Language Translation (IWSLT), San Francisco, USA, 2011. [slides]
  35. 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. Workshop on Statistical Machine Translation (WMT), 2011. [poster]
  36. A. Sokolov and F. Yvon. Minimum error rate training semiring. European Association for Machine Translation (EAMT), 2011. [slides]
  37. A. Sokolov, T. Urvoy, L. Denoyer, and O. Ricard. MADSPAM consortium at the ECML/PKDD Discovery Challenge 2010. ECML Discovery Challenge Workshop (Discovery@ECML-PKDD), 2010. ECML/PKDD Discovery Challenge: 1st place at the English quality task & 2nd place @ general task. [slides]
  38. 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. [slides in english] [resume in ukrainian] [full pdf in russian] [slides in russian]
  39. 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]
  40. A. Sokolov. Randomized edit distance embedding in gene finding and intrusion detection. Journal of System Technologies, (2):126-139. 2008. [pdf in russian]
  41. 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]
  42. A. Sokolov. Searching for nearest strings with neural-like string embeddings. Journal of Information Theories and Applications, 14(3):294-299. 2007.
  43. A. Sokolov. Nearest string by neural-like encoding. Knowledge-Dialogue-Solution (KDS), 2006.
  44. A. Sokolov and D. Rachkovskij. Approaches to sequence similarity representation. Journal of Information Theories and Applications, 13(3):272-278. 2005.
  45. A. Sokolov and D. Rachkovskij. Some approaches to distributed encoding of sequences. Knowledge-Dialogue-Solution (KDS), volume 2, pages 522-528, 2005.
  46. 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. [pdf in russian]
  47. I. Misuno, D. Rachkovskij, S. Slipchenko, and A. Sokolov. Processing text information with vector representations. Workshop on Inductive Modeling, pages 230-236, Kyiv, Ukraine, 2005.
  48. 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. [pdf in russian]
  49. 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]
  50. 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. [pdf in russian]
  51. 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]
  52. 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]
  53. A. Sokolov and D. Rachkovskij. On handling replay attacks in intrusion detection systems. Journal of Information Theories and Applications, 10(3):341-348. 2003.
  54. A. Sokolov. An adaptive detection of anomalies in user's behavior. Int. Joint Conf. on Neural Networks (IJCNN), volume 4, pages 2443-2447, Portland, Oregon, USA, 2003.
  55. A. Sokolov. Detecting anomalies with markov chains with variable memory length. Artificial Intelligence, (4):74-83. 2002. [pdf in russian]
  56. 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.
  57. 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).
  58. A. Reznik, N. Kussul, and A. Sokolov. Identification of user activity using neural networks. Journal of Cybernetics and Computer Science, 123:70-79. 1999. [pdf in russian]
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