• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 71 matches

• 2024
• 
  Sebastian Bruch:
  Foundations of Vector Retrieval. Springer 2024, ISBN 978-3-031-55181-9, pp. 3-185
• 
  Sebastian Bruch, Siyu Gai, Amir Ingber:
  An Analysis of Fusion Functions for Hybrid Retrieval. ACM Trans. Inf. Syst. 42(1): 20:1-20:35 (2024)
• 
  Sebastian Bruch, Claudio Lucchese, Maria Maistro, Franco Maria Nardini:
  Special Section on Efficiency in Neural Information Retrieval. ACM Trans. Inf. Syst. 42(5): 113:1-113:4 (2024)
• 
  Sebastian Bruch, Franco Maria Nardini, Amir Ingber, Edo Liberty:
  An Approximate Algorithm for Maximum Inner Product Search over Streaming Sparse Vectors. ACM Trans. Inf. Syst. 42(2): 42:1-42:43 (2024)
• 
  Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini:
  Pairing Clustered Inverted Indexes with κ-NN Graphs for Fast Approximate Retrieval over Learned Sparse Representations. CIKM 2024: 3642-3646
• 
  Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini:
  Seismic: Efficient and Effective Retrieval over Learned Sparse Representation. IIR 2024: 103-106
• 
  Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini:
  Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations. SIGIR 2024: 152-162
• 
  Thomas Vecchiato, Claudio Lucchese, Franco Maria Nardini, Sebastian Bruch:
  A Learning-to-Rank Formulation of Clustering-Based Approximate Nearest Neighbor Search. SIGIR 2024: 2261-2265
• 
  Sebastian Bruch:
  Foundations of Vector Retrieval. CoRR abs/2401.09350 (2024)
• 
  Thomas Vecchiato, Claudio Lucchese, Franco Maria Nardini, Sebastian Bruch:
  A Learning-to-Rank Formulation of Clustering-Based Approximate Nearest Neighbor Search. CoRR abs/2404.11731 (2024)
• 
  Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini:
  Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations. CoRR abs/2404.18812 (2024)
• 
  Sebastian Bruch, Aditya Krishnan, Franco Maria Nardini:
  Optimistic Query Routing in Clustering-based Approximate Maximum Inner Product Search. CoRR abs/2405.12207 (2024)
• 
  Sebastian Bruch, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini:
  Pairing Clustered Inverted Indexes with kNN Graphs for Fast Approximate Retrieval over Learned Sparse Representations. CoRR abs/2408.04443 (2024)
• 2023
• 
  Nima Esmi, Yasaman Golshan, Sara Asadi, Asadollah Shahbahrami, Georgi Gaydadjiev:
  A fuzzy fine-tuned model for COVID-19 diagnosis. Comput. Biol. Medicine 153: 106483 (2023)
• 
  Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini:
  Efficient and Effective Tree-based and Neural Learning to Rank. Found. Trends Inf. Retr. 17(1): 1-123 (2023)
• 
  Seyed-Sajad Ahmadpour, Arash Heidari, Nima Jafari Navimipour, Mohammad-Ali Asadi, Senay Yalçin:
  An Efficient Design of Multiplier for Using in Nano-Scale IoT Systems Using Atomic Silicon. IEEE Internet Things J. 10(16): 14908-14909 (2023)
• 
  Mathieu Guillame-Bert, Sebastian Bruch, Richard Stotz, Jan Pfeifer:
  Yggdrasil Decision Forests: A Fast and Extensible Decision Forests Library. KDD 2023: 4068-4077
• 
  Sebastian Bruch, Joel Mackenzie, Maria Maistro, Franco Maria Nardini:
  ReNeuIR at SIGIR 2023: The Second Workshop on Reaching Efficiency in Neural Information Retrieval. SIGIR 2023: 3456-3459
• 
  Julius Adelt, Sebastian Bruch, Paula Herber, Mathis Niehage, Anne Remke:
  Shielded Learning for Resilience and Performance Based on Statistical Model Checking in Simulink. AISoLA 2023: 94-118
• 
  Salvatore Orlando, Gabriella Pasi, Sebastian Bruch, Claudio Lucchese, Xiaohui Tao:
  Preface WI-IAT 2023. WI/IAT 2023: xviii-xxi
• 
  Sebastian Bruch, Franco Maria Nardini, Amir Ingber, Edo Liberty:
  An Approximate Algorithm for Maximum Inner Product Search over Streaming Sparse Vectors. CoRR abs/2301.10622 (2023)
• 
  Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini:
  Efficient and Effective Tree-based and Neural Learning to Rank. CoRR abs/2305.08680 (2023)
• 
  Sebastian Bruch, Franco Maria Nardini, Amir Ingber, Edo Liberty:
  Bridging Dense and Sparse Maximum Inner Product Search. CoRR abs/2309.09013 (2023)
• 2022
• 
  Jamshid Shakeri, Mostafa Asadizadeh, Nima Babanouri:
  The prediction of dynamic energy behavior of a Brazilian disk containing nonpersistent joints subjected to drop hammer test utilizing heuristic approaches. Neural Comput. Appl. 34(12): 9777-9792 (2022)
• 
  Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini:
  Report on the 1st Workshop on Reaching Efficiency in Neural Information Retrieval (ReNeuIR 2022) at SIGIR 2022. SIGIR Forum 56(2): 12:1-12:14 (2022)
• 
  Sebastian Bruch, Claudio Lucchese, Franco Maria Nardini:
  ReNeuIR: Reaching Efficiency in Neural Information Retrieval. SIGIR 2022: 3462-3465
• 
  Sebastian Bruch, Siyu Gai, Amir Ingber:
  An Analysis of Fusion Functions for Hybrid Retrieval. CoRR abs/2210.11934 (2022)
• 
  Mathieu Guillame-Bert, Sebastian Bruch, Richard Stotz, Jan Pfeifer:
  Yggdrasil Decision Forests: A Fast and Extensible Decision Forests Library. CoRR abs/2212.02934 (2022)
• 2021
• 
  Sebastian Bruch:
  An Alternative Cross Entropy Loss for Learning-to-Rank. WWW 2021: 118-126
• 2020
• 
  Sebastian Bruch, Shuguang Han, Michael Bendersky, Marc Najork:
  A Stochastic Treatment of Learning to Rank Scoring Functions. WSDM 2020: 61-69

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