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Noam Koenigstein
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2020 – today
- 2025
- [j7]Ori Katz
, Oren Barkan
Personalized Cadence Awareness for Next Basket Recommendation. Trans. Recomm. Syst. 3(1): 6:1-6:23 (2025) - 2024
- [j6]Oren Barkan, Tom Shaked, Yonatan Fuchs, Noam Koenigstein
Modeling users' heterogeneous taste with diversified attentive user profiles. User Model. User Adapt. Interact. 34(2): 375-405 (2024) - [c63]Yakir Yehuda, Itzik Malkiel, Oren Barkan, Jonathan Weill, Royi Ronen, Noam Koenigstein:
InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers. ACL (1) 2024: 9333-9347 - [c62]Oren Barkan, Yonatan Toib, Yehonatan Elisha, Noam Koenigstein:
A Learning-based Approach for Explaining Language Models. CIKM 2024: 98-108 - [c61]Yehonatan Elisha, Oren Barkan, Noam Koenigstein:
Probabilistic Path Integration with Mixture of Baseline Distributions. CIKM 2024: 570-580 - [c60]Oren Barkan, Yehonatan Elisha, Yonatan Toib, Jonathan Weill, Noam Koenigstein:
Improving LLM Attributions with Randomized Path-Integration. EMNLP (Findings) 2024: 9430-9446 - [c59]Oren Barkan, Yonatan Toib, Yehonatan Elisha, Jonathan Weill, Noam Koenigstein:
LLM Explainability via Attributive Masking Learning. EMNLP (Findings) 2024: 9522-9537 - [c58]Itzik Malkiel, Yakir Yehuda, Jonathan Ephrath, Ori Katz, Oren Barkan, Nir Nice, Noam Koenigstein:
Unsupervised Topic-Conditional Extractive Summarization. ICASSP 2024: 11286-11290 - [c57]Itzik Malkiel, Uri Alon, Yakir Yehuda, Shahar Keren, Oren Barkan, Royi Ronen, Noam Koenigstein:
SEGLLM: Topic-Oriented Call Segmentation Via LLM-Based Conversation Synthesis. ICASSP 2024: 11361-11365 - [c56]Oren Barkan
A Counterfactual Framework for Learning and Evaluating Explanations for Recommender Systems. WWW 2024: 3723-3733 - [i27]Noy Uzrad, Oren Barkan, Almog Elharar, Shlomi Shvartzman, Moshe Laufer, Lior Wolf, Noam Koenigstein:
DiffMoog: a Differentiable Modular Synthesizer for Sound Matching. CoRR abs/2401.12570 (2024) - [i26]Yakir Yehuda, Itzik Malkiel, Oren Barkan, Jonathan Weill, Royi Ronen, Noam Koenigstein:
In Search of Truth: An Interrogation Approach to Hallucination Detection. CoRR abs/2403.02889 (2024) - 2023
- [j5]Keren Gaiger, Oren Barkan
Not All Memories Created Equal: Dynamic User Representations for Collaborative Filtering. IEEE Access 11: 34746-34763 (2023) - [c55]Oren Barkan
Deep Integrated Explanations. CIKM 2023: 57-67 - [c54]Itzik Malkiel
Harnessing GPT for Topic-Based Call Segmentation in Microsoft Dynamics 365 Sales. CIKM 2023: 5246-5247 - [c53]Oren Barkan, Yehonatan Elisha, Yuval Asher, Amit Eshel, Noam Koenigstein
Visual Explanations via Iterated Integrated Attributions. ICCV 2023: 2073-2084 - [c52]Oren Barkan, Tal Reiss, Jonathan Weill, Ori Katz, Roy Hirsch, Itzik Malkiel, Noam Koenigstein
Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond. ICCV 2023: 19950-19961 - [c51]Oren Barkan, Yehonatan Elisha, Jonathan Weill, Yuval Asher, Amit Eshel, Noam Koenigstein
Stochastic Integrated Explanations for Vision Models. ICDM 2023: 938-943 - [c50]Oren Barkan, Yuval Asher, Amit Eshel, Yehonatan Elisha, Noam Koenigstein
Learning to Explain: A Model-Agnostic Framework for Explaining Black Box Models. ICDM 2023: 944-949 - [c49]Oren Barkan, Shlomi Shvartzman, Noy Uzrad, Moshe Laufer, Almog Elharar, Noam Koenigstein:
Inversynth II: Sound Matching via Self-Supervised Synthesizer-Proxy and Inference-Time Finetuning. ISMIR 2023: 642-648 - [i25]Nitzan Farhi, Noam Koenigstein
Detecting Security Patches via Behavioral Data in Code Repositories. CoRR abs/2302.02112 (2023) - [i24]Itzik Malkiel, Uri Alon, Yakir Yehuda, Shahar Keren, Oren Barkan, Royi Ronen, Noam Koenigstein:
GPT-Calls: Enhancing Call Segmentation and Tagging by Generating Synthetic Conversations via Large Language Models. CoRR abs/2306.07941 (2023) - [i23]Oren Barkan, Avi Caciularu, Idan Rejwan, Ori Katz, Jonathan Weill, Itzik Malkiel, Noam Koenigstein:
Representation Learning via Variational Bayesian Networks. CoRR abs/2306.16326 (2023) - [i22]Oren Barkan, Tal Reiss, Jonathan Weill, Ori Katz, Roy Hirsch, Itzik Malkiel, Noam Koenigstein:
Efficient Discovery and Effective Evaluation of Visual Perceptual Similarity: A Benchmark and Beyond. CoRR abs/2308.14753 (2023) - [i21]Oren Barkan, Yehonatan Elisha, Jonathan Weill, Yuval Asher, Amit Eshel, Noam Koenigstein:
Deep Integrated Explanations. CoRR abs/2310.15368 (2023) - [i20]Oren Barkan, Yuval Asher, Amit Eshel, Yehonatan Elisha, Noam Koenigstein:
Learning to Explain: A Model-Agnostic Framework for Explaining Black Box Models. CoRR abs/2310.16584 (2023) - [i19]Oren Barkan, Yehonatan Elisha, Yuval Asher, Amit Eshel, Noam Koenigstein:
Visual Explanations via Iterated Integrated Attributions. CoRR abs/2310.18585 (2023) - 2022
- [c48]Itzik Malkiel, Dvir Ginzburg, Oren Barkan, Avi Caciularu, Yoni Weill, Noam Koenigstein
Metricbert: Text Representation Learning Via Self-Supervised Triplet Training. ICASSP 2022: 1-5 - [c47]Ori Katz, Oren Barkan, Noam Koenigstein
Learning to Ride a Buy-Cycle: A Hyper-Convolutional Model for Next Basket Repurchase Recommendation. RecSys 2022: 316-326 - [c46]Itzik Malkiel, Dvir Ginzburg, Oren Barkan, Avi Caciularu, Jonathan Weill, Noam Koenigstein
Interpreting BERT-based Text Similarity via Activation and Saliency Maps. WWW 2022: 3259-3268 - [i18]Oren Barkan, Edan Hauon, Avi Caciularu, Ori Katz, Itzik Malkiel, Omri Armstrong, Noam Koenigstein:
Grad-SAM: Explaining Transformers via Gradient Self-Attention Maps. CoRR abs/2204.11073 (2022) - [i17]Itzik Malkiel, Dvir Ginzburg, Oren Barkan, Avi Caciularu, Yoni Weill, Noam Koenigstein:
MetricBERT: Text Representation Learning via Self-Supervised Triplet Training. CoRR abs/2208.06610 (2022) - [i16]Itzik Malkiel, Dvir Ginzburg, Oren Barkan, Avi Caciularu, Jonathan Weill, Noam Koenigstein:
Interpreting BERT-based Text Similarity via Activation and Saliency Maps. CoRR abs/2208.06612 (2022) - 2021
- [c45]Dvir Ginzburg, Itzik Malkiel, Oren Barkan, Avi Caciularu, Noam Koenigstein
Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference. ACL/IJCNLP (Findings) 2021: 3088-3098 - [c44]Oren Barkan, Omri Armstrong, Amir Hertz, Avi Caciularu, Ori Katz, Itzik Malkiel, Noam Koenigstein
GAM: Explainable Visual Similarity and Classification via Gradient Activation Maps. CIKM 2021: 68-77 - [c43]Oren Barkan, Avi Caciularu, Idan Rejwan, Ori Katz, Jonathan Weill, Itzik Malkiel, Noam Koenigstein
Representation Learning via Variational Bayesian Networks. CIKM 2021: 78-88 - [c42]Oren Barkan, Roy Hirsch, Ori Katz, Avi Caciularu, Noam Koenigstein
Anchor-based Collaborative Filtering. CIKM 2021: 2877-2881 - [c41]Oren Barkan, Edan Hauon, Avi Caciularu, Ori Katz, Itzik Malkiel, Omri Armstrong, Noam Koenigstein
Grad-SAM: Explaining Transformers via Gradient Self-Attention Maps. CIKM 2021: 2882-2887 - [c40]Oren Barkan, Roy Hirsch, Ori Katz, Avi Caciularu, Yoni Weill, Noam Koenigstein
Cold Start Revisited: A Deep Hybrid Recommender with Cold-Warm Item Harmonization. ICASSP 2021: 3260-3264 - [c39]Oren Barkan, Roy Hirsch, Ori Katz, Avi Caciularu, Jonathan Weill, Noam Koenigstein
Cold Item Integration in Deep Hybrid Recommenders via Tunable Stochastic Gates. ICDM 2021: 994-999 - [i15]Dvir Ginzburg, Itzik Malkiel, Oren Barkan, Avi Caciularu, Noam Koenigstein:
Self-Supervised Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference. CoRR abs/2106.01186 (2021) - [i14]Oren Barkan, Omri Armstrong, Amir Hertz, Avi Caciularu, Ori Katz, Itzik Malkiel, Noam Koenigstein:
GAM: Explainable Visual Similarity and Classification via Gradient Activation Maps. CoRR abs/2109.00951 (2021) - [i13]Oren Barkan, Roy Hirsch, Ori Katz, Avi Caciularu, Jonathan Weill, Noam Koenigstein:
Cold Item Integration in Deep Hybrid Recommenders via Tunable Stochastic Gates. CoRR abs/2112.07615 (2021) - 2020
- [c38]Oren Barkan, Noam Razin, Itzik Malkiel, Ori Katz, Avi Caciularu, Noam Koenigstein:
Scalable Attentive Sentence Pair Modeling via Distilled Sentence Embedding. AAAI 2020: 3235-3242 - [c37]Oren Barkan, Idan Rejwan, Avi Caciularu, Noam Koenigstein
Bayesian Hierarchical Words Representation Learning. ACL 2020: 3871-3877 - [c36]Itzik Malkiel, Oren Barkan, Avi Caciularu, Noam Razin, Ori Katz, Noam Koenigstein:
Optimizing BERT for Unlabeled Text-Based Items Similarity. EMNLP (Findings) 2020: 1704-1714 - [c35]Oren Barkan, Ori Katz, Noam Koenigstein
Neural Attentive Multiview Machines. ICASSP 2020: 3357-3361 - [c34]Oren Barkan, Avi Caciularu, Ori Katz, Noam Koenigstein
Attentive Item2vec: Neural Attentive User Representations. ICASSP 2020: 3377-3381 - [c33]Oren Barkan, Avi Caciularu, Idan Rejwan, Ori Katz, Jonathan Weill, Itzik Malkiel, Noam Koenigstein
Cold Item Recommendations via Hierarchical Item2vec. ICDM 2020: 912-917 - [c32]Oren Barkan, Yonatan Fuchs, Avi Caciularu, Noam Koenigstein
Explainable Recommendations via Attentive Multi-Persona Collaborative Filtering. RecSys 2020: 468-473 - [e1]Rodrygo L. T. Santos, Leandro Balby Marinho, Elizabeth M. Daly, Li Chen, Kim Falk, Noam Koenigstein, Edleno Silva de Moura:
RecSys 2020: Fourteenth ACM Conference on Recommender Systems, Virtual Event, Brazil, September 22-26, 2020. ACM 2020, ISBN 978-1-4503-7583-2 [contents] - [i12]Oren Barkan, Avi Caciularu, Ori Katz, Noam Koenigstein:
Attentive Item2Vec: Neural Attentive User Representations. CoRR abs/2002.06205 (2020) - [i11]Oren Barkan, Ori Katz, Noam Koenigstein:
Neural Attentive Multiview Machines. CoRR abs/2002.07696 (2020) - [i10]Dor Bank, Noam Koenigstein, Raja Giryes:
Autoencoders. CoRR abs/2003.05991 (2020) - [i9]Oren Barkan, Idan Rejwan, Avi Caciularu, Noam Koenigstein:
Bayesian Hierarchical Words Representation Learning. CoRR abs/2004.07126 (2020) - [i8]Itzik Malkiel, Oren Barkan, Avi Caciularu, Noam Razin, Ori Katz, Noam Koenigstein:
RecoBERT: A Catalog Language Model for Text-Based Recommendations. CoRR abs/2009.13292 (2020) - [i7]Oren Barkan, Yonatan Fuchs, Avi Caciularu, Noam Koenigstein:
Explainable Recommendations via Attentive Multi-Persona Collaborative Filtering. CoRR abs/2010.07042 (2020)
2010 – 2019
- 2019
- [j4]Oren Barkan
InverSynth: Deep Estimation of Synthesizer Parameter Configurations From Audio Signals. IEEE ACM Trans. Audio Speech Lang. Process. 27(12): 2385-2396 (2019) - [c31]Oren Barkan, Noam Koenigstein
CB2CF: a neural multiview content-to-collaborative filtering model for completely cold item recommendations. RecSys 2019: 228-236 - [c30]Gal Lavee, Noam Koenigstein
When actions speak louder than clicks: a combined model of purchase probability and long-term customer satisfaction. RecSys 2019: 287-295 - [c29]Adi Makmal, Jonathan Ephrath, Hilik Berezin, Liron I. Allerhand, Nir Nice, Noam Koenigstein
Pick & merge: an efficient item filtering scheme for Windows store recommendations. RecSys 2019: 472-476 - [i6]Oren Barkan, Noam Razin, Itzik Malkiel, Ori Katz, Avi Caciularu, Noam Koenigstein:
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding. CoRR abs/1908.05161 (2019) - 2017
- [c28]Mike Gartrell, Ulrich Paquet, Noam Koenigstein:
Low-Rank Factorization of Determinantal Point Processes. AAAI 2017: 1912-1918 - [c27]Noam Koenigstein
Rethinking Collaborative Filtering: A Practical Perspective on State-of-the-art Research Based on Real World Insights. RecSys 2017: 336-337 - [c26]Shay Ben-Elazar, Gal Lavee, Noam Koenigstein
Groove Radio: A Bayesian Hierarchical Model for Personalized Playlist Generation. WSDM 2017: 445-453 - 2016
- [c25]Oren Barkan, Noam Koenigstein
ITEM2VEC: Neural item embedding for collaborative filtering. MLSP 2016: 1-6 - [c24]Oren Barkan, Yael Brumer, Noam Koenigstein:
Modelling Session Activity with Neural Embedding. RecSys Posters 2016 - [c23]Oren Barkan, Noam Koenigstein:
Item2vec: Neural Item Embedding for Collaborative Filtering. RecSys Posters 2016 - [c22]Mike Gartrell, Ulrich Paquet, Noam Koenigstein
Bayesian Low-Rank Determinantal Point Processes. RecSys 2016: 349-356 - [c21]Oren Sar Shalom, Noam Koenigstein
Beyond Collaborative Filtering: The List Recommendation Problem. WWW 2016: 63-72 - [i5]Mike Gartrell, Ulrich Paquet, Noam Koenigstein:
Low-Rank Factorization of Determinantal Point Processes for Recommendation. CoRR abs/1602.05436 (2016) - [i4]Oren Barkan, Noam Koenigstein:
Item2Vec: Neural Item Embedding for Collaborative Filtering. CoRR abs/1603.04259 (2016) - [i3]Mike Gartrell, Ulrich Paquet, Noam Koenigstein:
The Bayesian Low-Rank Determinantal Point Process Mixture Model. CoRR abs/1608.04245 (2016) - [i2]Oren Barkan, Noam Koenigstein, Eylon Yogev:
The Deep Journey from Content to Collaborative Filtering. CoRR abs/1611.00384 (2016) - 2014
- [c20]Yoram Bachrach, Yehuda Finkelstein, Ran Gilad-Bachrach
Speeding up the Xbox recommender system using a euclidean transformation for inner-product spaces. RecSys 2014: 257-264 - [c19]Shay Ben-Elazar, Noam Koenigstein:
A Hybrid Explanations Framework for Collaborative Filtering Recommender Systems. RecSys Posters 2014 - [c18]Allison June-Barlow Chaney, Mike Gartrell, Jake M. Hofman, John Guiver, Noam Koenigstein
A large-scale exploration of group viewing patterns. TVX 2014: 31-38 - [p1]Markus Schedl, Mohamed Sordo, Noam Koenigstein, Udi Weinsberg:
Mining User Generated Data for Music Information Retrieval. Mining User Generated Content 2014: 67-96 - 2013
- [c17]Noam Koenigstein
Xbox movies recommendations: variational bayes matrix factorization with embedded feature selection. RecSys 2013: 129-136 - [c16]Royi Ronen, Noam Koenigstein
Selecting content-based features for collaborative filtering recommenders. RecSys 2013: 407-410 - [c15]Noam Koenigstein
Towards scalable and accurate item-oriented recommendations. RecSys 2013: 419-422 - [c14]Royi Ronen, Noam Koenigstein
Sage: recommender engine as a cloud service. RecSys 2013: 475-476 - [c13]Ulrich Paquet, Noam Koenigstein
One-class collaborative filtering with random graphs. WWW 2013: 999-1008 - [i1]Ulrich Paquet, Noam Koenigstein:
One-class Collaborative Filtering with Random Graphs: Annotated Version. CoRR abs/1309.6786 (2013) - 2012
- [j3]Noam Koenigstein
Talent scouting in P2P networks. Comput. Networks 56(3): 970-982 (2012) - [j2]Noam Koenigstein
Measuring the validity of peer-to-peer data for information retrieval applications. Comput. Networks 56(3): 1092-1102 (2012) - [j1]Gideon Dror, Noam Koenigstein
Web-Scale Media Recommendation Systems. Proc. IEEE 100(9): 2722-2736 (2012) - [c12]Noam Koenigstein
Efficient retrieval of recommendations in a matrix factorization framework. CIKM 2012: 535-544 - [c11]Noam Koenigstein
The Xbox recommender system. RecSys 2012: 281-284 - [c10]Gideon Dror, Noam Koenigstein, Yehuda Koren, Markus Weimer:
The Yahoo! Music Dataset and KDD-Cup '11. KDD Cup 2012: 8-18 - 2011
- [c9]Noam Koenigstein
Yahoo! music recommendations: modeling music ratings with temporal dynamics and item taxonomy. RecSys 2011: 165-172 - 2010
- [c8]Noam Koenigstein
A framework for extracting musical similarities from peer-to-peer networks. ICME 2010: 1433-1438 - [c7]Markus Schedl, Tim Pohle, Noam Koenigstein, Peter Knees:
What's Hot? Estimating Country-specific Artist Popularity. ISMIR 2010: 117-122 - [c6]Noam Koenigstein, Gert R. G. Lanckriet, Brian McFee, Yuval Shavitt:
Collaborative Filtering Based on P2P Networks. ISMIR 2010: 153-158 - [c5]Noam Koenigstein, Yuval Shavitt, Ela Weinsberg, Udi Weinsberg:
On the Applicability of Peer-to-peer Data in Music Information Retrieval Research. ISMIR 2010: 273-278 - [c4]Pavel Gurvich, Noam Koenigstein
Analyzing the DC File Sharing Network. Peer-to-Peer Computing 2010: 1-4
2000 – 2009
- 2009
- [c3]Noam Koenigstein
Predicting Billboard Success Using Data-Mining in P2P Networks. ISM 2009: 465-470 - [c2]Noam Koenigstein, Yuval Shavitt:
Song Ranking based on Piracy in Peer-to-Peer Networks. ISMIR 2009: 633-638 - 2008
- [c1]Noam Koenigstein
Spotting out emerging artists using geo-aware analysis of P2P query strings. KDD 2008: 937-945
Coauthor Index
[j7] [j6] [c63] [c62] [c61] [c60] [c59] [c58] [c57] [c56] [i27] [i26] [j5] [c55] [c54] [c53] [c52] [c51] [c50] [c49] [i24] [i23] [i22] [i21] [i20] [i19] [c48] [c47] [c46] [i18] [i17] [i16] [c45] [c44] [c43] [c42] [c41] [c40] [c39] [i15] [i14] [i13] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [i12] [i11] [i9] [i8] [i7] [j4] [c31] [c30] [i6] [c26] [c25] [c24] [c23] [i4] [i2]
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