劉鐵岩

劉鐵岩博士是機器學習和信息檢索領域的知名專家，尤其在排序學習方面取得了國際領先的研究成果。他著有《排序學習及其在信息檢索中的應用》等學術專著。他在國際頂級期刊和會議上發表相關論文70餘篇。他持有40餘項美國和國際專利。他的論文曾獲得國際信息檢索大會(SIGIR)最佳學生論文獎，和國際期刊《視覺通信和圖像表示》的最高引用論文獎。

他是國際計算機輔助搜索會議(RIAO) 2010年度的程序委員會主席，國際信息檢索大會(SIGIR)2008-2011年度的領域主席(Area Chair)，亞洲信息檢索會議(AIRS) 2009-2011年度的領域主席，國際數據挖掘大會（KDD）2012年度的展覽和演示主席，國際網際網路大會（WWW）2011年度的領域主席。他擔任美國計算機學會會刊《信息系統（TOIS）》的副主編，國際期刊《信息檢索》和《人工智慧》的編委，和數十個國際期刊的審稿專家。他是包括WWW, SIGIR, ICML, ACL, ICIP等在內的三十幾個國際會議的程序委員會成員(Program Committee Member)，是國際排序學習研討會(LR4IR)2007-2009年度的聯合主席(Co-chair)，和2010年排序學習競賽的聯合組織者。他曾經在WWW、SIGIR、KDD等國際會議上做關於排序學習的主題講座(tutorial)，並受邀作為KDD 2011年度的大會主題辯論嘉賓(panelist)。他受邀為亞太多媒體大會（PCM 2010）和中國信息檢索大會（CCIR 2011）做大會特邀報告（keynote）。他還受邀為包括卡耐基梅隆大學（CMU）在內的十餘所國內外高校講授《排序學習》和《機器學習》的課程。

Internet Economics

● Joint Optimization of Bid and Budget Allocation in Sponsored Search, KDD 2012

● Relational Click Prediction for Sponsored Search, WSDM 2012.

● An Advertiser-Centric Approach to Understand User Click Behavior in Sponsored Search, CIKM 2011.

Learning to Rank

● Learning to Rank for Information Retrieval, Foundation and Trends on Information Retrieval, Now Publishers, 2009.

● A Noise-Tolerant Graphical Model for Ranking, Information Processing and Management, 2011.

● Future research directions on learning to rank, Proceeding track, Journal of Machine Learning Research, 2011.

● Selecting Optimal Training Data for Learning to Rank, Information Processing and Management, 2011.

● A New Probabilistic Model for Rank Aggregation, NIPS 2010.

● Two-Layer Generalization Analysis for Ranking Using Rademacher Average, NIPS 2010.

● Statistical Consistency of Top-k Ranking, NIPS 2009.

● Ranking Measures and Loss Functions in Learning to Rank, NIPS 2009.

● Global Ranking Using Continuous Conditional Random Fields, NIPS 2008.

● Generalization Analysis of Listwise Learning to Rank Algorithms, ICML 2009.

● Listwise Approach to Learning to Rank: Theorem and Algorithm, ICML 2008.

● Query-level Stability and Generalization in Learning to Rank, ICML 2008.

● Learning to Rank: From Pairwise Approach to Listwise Approach. ICML 2007.

● Query-dependent Ranking using K-Nearest Neighbor, SIGIR 2008.

● Directly Optimizing IR Evaluation Measures in Learning to Rank, SIGIR 2008.

● Making LETOR More Useful and Reliable, LR4IR 2008, in conjunction with SIGIR 2008.

● Feature Selection for Ranking, SIGIR 2007.

● FRank:A Ranking Method with Fidelity Loss, SIGIR 2007.

● Ranking with Multiple Hyperplanes, SIGIR 2007.

● LETOR: Benchmark dataset for research on learning to rank for information retrieval, LR4IR 2007, in conjunction with SIGIR 2007.

● Adapting Ranking SVM to Document Retrieval, SIGIR 2006.

● Learning to Rank Relational Objects and Its Application to Web Search, WWW 2008.

● Supervised Rank Aggregation, WWW 2007.

● Ranking with query-dependent loss for web search. WSDM 2010

● Tendency Correlation Analysis for Direct Optimization of Evaluation Measures in Information Retrieval, Information Retrieval Journal, 2010.

● Introduction to special issue on learning to rank for information retrieval, Information Retrieval Journal, 2010.

● A General Approximation Framework for Direct Optimization of Information Retrieval Measures, Information Retrieval Journal, 2009.

Web Search

● Semi-supervised graph ranking with rich meta data, KDD 2011.

● Page Importance Computation based on Markov Processes, Information Retrieval, 2011

● Let Web Spammers Expose Themselves, WSDM 2011.

● Actively Predicting Diverse Search Intent from User Browsing Behaviors, WWW 2010.

● A Framework to Compute Page Importance based on User Behaviors, Information Retrieval Journal, 2009.

● BrowseRank: Letting Web Users Vote for Page Importance, SIGIR 2008.[SIGIR Best Student Paper Award]

● AggregateRank: Bringing Order to Websites, SIGIR 2006.

● A Study on Relevance Propagation for Web Search, SIGIR 2005.

● Time-Dependent Semantic Similarity Measure of Queries Using Historical Click-Through Data, WWW 2006.

● Event Detection from Evolution of Click-through Data, KDD 2006.

● Consistent Bipartite Graph Co-Partitioning for Star-Structured High-Order Heterogeneous Data Co-Clustering, KDD 2005.

● Ranking Websites: A Probabilistic View, Internet Mathematics, 2007.

● Hierarchical Taxonomy Preparation for Text Categorization Using Consistent Bipartite Spectral Graph Co-partitioning, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2005.

● Support Vector Machines Classification with Very Large Scale Taxonomy, SIGKDD Explorations, 2005.

Multimedia

● A New Cut Detection Algorithm with Constant False-Alarm Ratio for Video Segmentation, Journal of Visual Communications and Image Representation, 2004.[Most Cited Paper Award]

● Shot Reconstruction Degree: a Novel Criterion for Key Frame Selection, Pattern Recognition Letters, 2004.

● Frame Interpolation Scheme Using Inertia Motion Prediction. Signal Processing: Image Communication, 2003.

● Inertia-based Cut Detection and Its Integration with Video Coder. IEE Proceedings on Vision, Image and Signal Processing, 2003.