Sebastian Bruch

According to our database, Sebastian Bruch authored at least 37 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

An Approximate Algorithm for Maximum Inner Product Search over Streaming Sparse Vectors.

Sebastian Bruch, Franco Maria Nardini, Amir Ingber, Edo Liberty

ACM Trans. Inf. Syst., March, 2024

An Analysis of Fusion Functions for Hybrid Retrieval.

Sebastian Bruch, Siyu Gai, Amir Ingber

ACM Trans. Inf. Syst., January, 2024

Foundations of Vector Retrieval.

Sebastian Bruch

CoRR, 2024

Foundations of Vector Retrieval

Sebastian Bruch

Springer, ISBN: 978-3-031-55181-9, 2024

2023

Efficient and Effective Tree-based and Neural Learning to Rank.

Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini

Found. Trends Inf. Retr., 2023

Bridging Dense and Sparse Maximum Inner Product Search.

Sebastian Bruch, Franco Maria Nardini, Amir Ingber, Edo Liberty

CoRR, 2023

Preface WI-IAT 2023.

Salvatore Orlando, Gabriella Pasi, Sebastian Bruch, Claudio Lucchese, Xiaohui Tao

Proceedings of the IEEE International Conference on Web Intelligence and Intelligent Agent Technology, 2023

Shielded Learning for Resilience and Performance Based on Statistical Model Checking in Simulink.

Julius Adelt, Sebastian Bruch, Paula Herber, Mathis Niehage, Anne Remke

Proceedings of the Bridging the Gap Between AI and Reality, 2023

ReNeuIR at SIGIR 2023: The Second Workshop on Reaching Efficiency in Neural Information Retrieval.

Sebastian Bruch, Joel Mackenzie, Maria Maistro, Franco Maria Nardini

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Yggdrasil Decision Forests: A Fast and Extensible Decision Forests Library.

Mathieu Guillame-Bert, Sebastian Bruch, Richard Stotz, Jan Pfeifer

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Report on the 1st Workshop on Reaching Efficiency in Neural Information Retrieval (ReNeuIR 2022) at SIGIR 2022.

Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini

SIGIR Forum, December, 2022

ReNeuIR: Reaching Efficiency in Neural Information Retrieval.

Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

2021

An Alternative Cross Entropy Loss for Learning-to-Rank.

Sebastian Bruch

Proceedings of the WWW '21: The Web Conference 2021, 2021

2020

Modeling Text with Decision Forests using Categorical-Set Splits.

Mathieu Guillame-Bert, Sebastian Bruch, Petr Mitrichev, Petr Mikheev, Jan Pfeifer

CoRR, 2020

Learning Representations for Axis-Aligned Decision Forests through Input Perturbation.

Sebastian Bruch, Jan Pfeifer, Mathieu Guillame-Bert

CoRR, 2020

A Stochastic Treatment of Learning to Rank Scoring Functions.

Sebastian Bruch, Shuguang Han, Michael Bendersky, Marc Najork

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

2019

Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning.

Claudio Lucchese, Franco Maria Nardini, Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang, Harrie Oosterhuis, Rolf Jagerman, Maarten de Rijke

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Revisiting Approximate Metric Optimization in the Age of Deep Neural Networks.

Sebastian Bruch, Masrour Zoghi, Michael Bendersky, Marc Najork

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank.

Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Neural Learning to Rank using TensorFlow Ranking: A Hands-on Tutorial.

Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang

Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval, 2019

An Analysis of the Softmax Cross Entropy Loss for Learning-to-Rank with Binary Relevance.

Sebastian Bruch, Xuanhui Wang, Michael Bendersky, Marc Najork

Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval, 2019

Learning Groupwise Multivariate Scoring Functions Using Deep Neural Networks.

Qingyao Ai, Xuanhui Wang, Sebastian Bruch, Nadav Golbandi, Michael Bendersky, Marc Najork

Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval, 2019

2014

Runtime Optimizations for Tree-Based Machine Learning Models.

Nima Asadi, Jimmy Lin, Arjen P. de Vries

IEEE Trans. Knowl. Data Eng., 2014

2013

Multi-Stage Search Architectures for Streaming Documents.

Nima Asadi

PhD thesis, 2013

Fast candidate generation for real-time tweet search with bloom filter chains.

Nima Asadi, Jimmy Lin

ACM Trans. Inf. Syst., 2013

Document vector representations for feature extraction in multi-stage document ranking.

Nima Asadi, Jimmy Lin

Inf. Retr., 2013

Fast, Incremental Inverted Indexing in Main Memory for Web-Scale Collections

Nima Asadi, Jimmy Lin

CoRR, 2013

Effectiveness/efficiency tradeoffs for candidate generation in multi-stage retrieval architectures.

Nima Asadi, Jimmy Lin

Proceedings of the 36th International ACM SIGIR conference on research and development in Information Retrieval, 2013

Dynamic memory allocation policies for postings in real-time Twitter search.

Nima Asadi, Jimmy Lin, Michael Busch

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Training Efficient Tree-Based Models for Document Ranking.

Nima Asadi, Jimmy Lin

Proceedings of the Advances in Information Retrieval, 2013

2012

Runtime Optimizations for Prediction with Tree-Based Models

Nima Asadi, Jimmy Lin, Arjen P. de Vries

CoRR, 2012

Mr. LDA: a flexible large scale topic modeling package using variational inference in MapReduce.

Ke Zhai, Jordan L. Boyd-Graber, Nima Asadi, Mohamad L. Alkhouja

Proceedings of the 21st World Wide Web Conference 2012, 2012

Fast candidate generation for two-phase document ranking: postings list intersection with bloom filters.

Nima Asadi, Jimmy Lin

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011

Using Variational Inference and MapReduce to Scale Topic Modeling

Ke Zhai, Jordan L. Boyd-Graber, Nima Asadi

CoRR, 2011

Cross-corpus relevance projection.

Nima Asadi, Donald Metzler, Jimmy Lin

Proceedings of the Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2011

Pseudo test collections for learning web search ranking functions.

Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy Lin

Proceedings of the Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2011

2010

UMD and USC/ISI: TREC 2010 Web Track Experiments with Ivory.

Tamer Elsayed, Nima Asadi, Lidan Wang, Jimmy Lin, Donald Metzler

Proceedings of The Nineteenth Text REtrieval Conference, 2010