Sebastian Bruch

64 papers A* 15A 5Misc 4Journal 32Unranked 6
YearRankTypeTitle / Venue / Authors
2026 — conf
Forward Index Compression for Learned Sparse Retrieval.
ECIR (2)
Sebastian Bruch, Martino Fontana, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini
2026 J jnl
Forward Index Compression for Learned Sparse Retrieval.
CoRR
Sebastian Bruch, Martino Fontana, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini
2026 J jnl
Neighborhood Stability as a Measure of Nearest Neighbor Searchability.
CoRR
Thomas Vecchiato, Sebastian Bruch
2025 A conf
Advances in Vector Search.
WSDM
Sebastian Bruch
2025 J jnl
Efficient Sketching and Nearest Neighbor Search Algorithms for Sparse Vector Sets.
CoRR
Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini
2025 — conf
Investigating the Scalability of Approximate Sparse Retrieval Algorithms to Massive Datasets.
ECIR (3)
Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini, Leonardo Venuta
2025 J jnl
Investigating the Scalability of Approximate Sparse Retrieval Algorithms to Massive Datasets.
CoRR
Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini, Leonardo Venuta
2025 Misc ed.
Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval, ICTIR 2025, Padua, Italy, 18 July 2025
ICTIR
Hamed Zamani, Laura Dietz, Benjamin Piwowarski, Sebastian Bruch
2025 A* conf
ReNeuIR at SIGIR 2025: The Fourth Workshop on Reaching Efficiency in Neural Information Retrieval.
SIGIR
Sebastian Bruch, Maik Fröbe, Tim Hagen, Franco Maria Nardini, Martin Potthast
2025 J jnl
Uncovering Visual-Semantic Psycholinguistic Properties from the Distributional Structure of Text Embedding Spac.
CoRR
Si Wu, Sebastian Bruch
2025 — conf
Uncovering Visual-Semantic Psycholinguistic Properties from the Distributional Structure of Text Embedding Space.
ACL (1)
Si Wu, Sebastian Bruch
2024 A* conf
A Learning-to-Rank Formulation of Clustering-Based Approximate Nearest Neighbor Search.
SIGIR
Thomas Vecchiato, Claudio Lucchese, Franco Maria Nardini, Sebastian Bruch
2024 J jnl
A Learning-to-Rank Formulation of Clustering-Based Approximate Nearest Neighbor Search.
CoRR
Thomas Vecchiato, Claudio Lucchese, Franco Maria Nardini, Sebastian Bruch
2024 J jnl
An Analysis of Fusion Functions for Hybrid Retrieval.
ACM Trans. Inf. Syst.
Sebastian Bruch, Siyu Gai, Amir Ingber
2024 J jnl
An Approximate Algorithm for Maximum Inner Product Search over Streaming Sparse Vectors.
ACM Trans. Inf. Syst.
Sebastian Bruch, Franco Maria Nardini, Amir Ingber, Edo Liberty
2024 J jnl
Bridging Dense and Sparse Maximum Inner Product Search.
ACM Trans. Inf. Syst.
Sebastian Bruch, Franco Maria Nardini, Amir Ingber, Edo Liberty
2024 J jnl
Efficient Inverted Index-based Approximate Retrieval over High-dimensional Learned Sparse Representations.
IEEE Data Eng. Bull.
Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini
2024 A* conf
Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations.
SIGIR
Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini
2024 J jnl
Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations.
CoRR
Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini
2024 — book
Foundations of Vector Retrieval
Sebastian Bruch
2024 J jnl
Foundations of Vector Retrieval.
CoRR
Sebastian Bruch
2024 J jnl
Optimistic Query Routing in Clustering-based Approximate Maximum Inner Product Search.
CoRR
Sebastian Bruch, Aditya Krishnan, Franco Maria Nardini
2024 J jnl
Pairing Clustered Inverted Indexes with kNN Graphs for Fast Approximate Retrieval over Learned Sparse Representations.
CoRR
Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini
2024 A conf
Pairing Clustered Inverted Indexes with κ-NN Graphs for Fast Approximate Retrieval over Learned Sparse Representations.
CIKM
Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini
2024 — conf
Seismic: Efficient and Effective Retrieval over Learned Sparse Representation.
IIR
Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini
2024 J jnl
Special Section on Efficiency in Neural Information Retrieval.
ACM Trans. Inf. Syst.
Sebastian Bruch, Claudio Lucchese, Maria Maistro, Franco Maria Nardini
2023 J jnl
An Approximate Algorithm for Maximum Inner Product Search over Streaming Sparse Vectors.
CoRR
Sebastian Bruch, Franco Maria Nardini, Amir Ingber, Edo Liberty
2023 J jnl
Bridging Dense and Sparse Maximum Inner Product Search.
CoRR
Sebastian Bruch, Franco Maria Nardini, Amir Ingber, Edo Liberty
2023 J jnl
Efficient and Effective Tree-based and Neural Learning to Rank.
CoRR
Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini
2023 J jnl
Efficient and Effective Tree-based and Neural Learning to Rank.
Found. Trends Inf. Retr.
Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini
2023 — conf
Preface WI-IAT 2023.
WI/IAT
Salvatore Orlando, Gabriella Pasi, Sebastian Bruch, Claudio Lucchese, Xiaohui Tao
2023 A* conf
ReNeuIR at SIGIR 2023: The Second Workshop on Reaching Efficiency in Neural Information Retrieval.
SIGIR
Sebastian Bruch, Joel Mackenzie, Maria Maistro, Franco Maria Nardini
2023 A* conf
Yggdrasil Decision Forests: A Fast and Extensible Decision Forests Library.
KDD
Mathieu Guillame-Bert, Sebastian Bruch, Richard Stotz, Jan Pfeifer
2022 J jnl
An Analysis of Fusion Functions for Hybrid Retrieval.
CoRR
Sebastian Bruch, Siyu Gai, Amir Ingber
2022 A* conf
ReNeuIR: Reaching Efficiency in Neural Information Retrieval.
SIGIR
Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini
2022 J jnl
Report on the 1st Workshop on Reaching Efficiency in Neural Information Retrieval (ReNeuIR 2022) at SIGIR 2022.
SIGIR Forum
Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini
2022 J jnl
Yggdrasil Decision Forests: A Fast and Extensible Decision Forests Library.
CoRR
Mathieu Guillame-Bert, Sebastian Bruch, Richard Stotz, Jan Pfeifer
2021 A* conf
An Alternative Cross Entropy Loss for Learning-to-Rank.
WWW
Sebastian Bruch
2020 A conf
A Stochastic Treatment of Learning to Rank Scoring Functions.
WSDM
Sebastian Bruch, Shuguang Han, Michael Bendersky, Marc Najork
2020 J jnl
Learning Representations for Axis-Aligned Decision Forests through Input Perturbation.
CoRR
Sebastian Bruch, Jan Pfeifer, Mathieu Guillame-Bert
2020 J jnl
Modeling Text with Decision Forests using Categorical-Set Splits.
CoRR
Mathieu Guillame-Bert, Sebastian Bruch, Petr Mitrichev, Petr Mikheev, Jan Pfeifer
2019 Misc conf
An Analysis of the Softmax Cross Entropy Loss for Learning-to-Rank with Binary Relevance.
ICTIR
Sebastian Bruch, Xuanhui Wang, Michael Bendersky, Marc Najork
2019 Misc conf
Learning Groupwise Multivariate Scoring Functions Using Deep Neural Networks.
ICTIR
Qingyao Ai, Xuanhui Wang, Sebastian Bruch, Nadav Golbandi, Michael Bendersky, Marc Najork
2019 A* conf
Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning.
SIGIR
Claudio Lucchese, Franco Maria Nardini, Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang, Harrie Oosterhuis, Rolf Jagerman, Maarten de Rijke
2019 Misc conf
Neural Learning to Rank using TensorFlow Ranking: A Hands-on Tutorial.
ICTIR
Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang
2019 A* conf
Revisiting Approximate Metric Optimization in the Age of Deep Neural Networks.
SIGIR
Sebastian Bruch, Masrour Zoghi, Michael Bendersky, Marc Najork
2019 A* conf
TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank.
KDD
Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf
2018 J jnl
TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank.
CoRR
Rama Kumar Pasumarthi, Xuanhui Wang, Cheng Li, Sebastian Bruch, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf
2014 J jnl
Runtime Optimizations for Tree-Based Machine Learning Models.
IEEE Trans. Knowl. Data Eng.
Sebastian Bruch, Jimmy Lin, Arjen P. de Vries
2013 J jnl
Document vector representations for feature extraction in multi-stage document ranking.
Inf. Retr.
Sebastian Bruch, Jimmy Lin
2013 J jnl
Dynamic Memory Allocation Policies for Postings in Real-Time Twitter Search
CoRR
Sebastian Bruch, Jimmy Lin, Michael Busch
2013 A* conf
Dynamic memory allocation policies for postings in real-time Twitter search.
KDD
Sebastian Bruch, Jimmy Lin, Michael Busch
2013 A* conf
Effectiveness/efficiency tradeoffs for candidate generation in multi-stage retrieval architectures.
SIGIR
Sebastian Bruch, Jimmy Lin
2013 J jnl
Fast candidate generation for real-time tweet search with bloom filter chains.
ACM Trans. Inf. Syst.
Sebastian Bruch, Jimmy Lin
2013 J jnl
Fast, Incremental Inverted Indexing in Main Memory for Web-Scale Collections
CoRR
Sebastian Bruch, Jimmy Lin
2013 — —
Multi-Stage Search Architectures for Streaming Documents.
Sebastian Bruch
2013 A conf
Training Efficient Tree-Based Models for Document Ranking.
ECIR
Sebastian Bruch, Jimmy Lin
2012 A conf
Fast candidate generation for two-phase document ranking: postings list intersection with bloom filters.
CIKM
Sebastian Bruch, Jimmy Lin
2012 A* conf
Mr. LDA: a flexible large scale topic modeling package using variational inference in MapReduce.
WWW
Ke Zhai, Jordan L. Boyd-Graber, Sebastian Bruch, Mohamad L. Alkhouja
2012 J jnl
Runtime Optimizations for Prediction with Tree-Based Models
CoRR
Sebastian Bruch, Jimmy Lin, Arjen P. de Vries
2011 A* conf
Cross-corpus relevance projection.
SIGIR
Sebastian Bruch, Donald Metzler, Jimmy Lin
2011 A* conf
Pseudo test collections for learning web search ranking functions.
SIGIR
Sebastian Bruch, Donald Metzler, Tamer Elsayed, Jimmy Lin
2011 J jnl
Using Variational Inference and MapReduce to Scale Topic Modeling
CoRR
Ke Zhai, Jordan L. Boyd-Graber, Sebastian Bruch
2010 — conf
UMD and USC/ISI: TREC 2010 Web Track Experiments with Ivory.
TREC
Tamer Elsayed, Sebastian Bruch, Lidan Wang, Jimmy Lin, Donald Metzler