個人資料
劉鐵巖博士是機器學習和信息檢索領(lǐng)域的知名專家，尤其在排序?qū)W習方面取得了國際領(lǐng)先的研究成果。他著有《排序?qū)W習及其在信息檢索中的應(yīng)用》等學術(shù)專著。他在國際頂級期刊和會議上發(fā)表相關(guān)論文70余篇。他持有40余項美國和國際專利。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(lǐng)域主席(Area Chair)，亞洲信息檢索會議(AIRS) 2009-2011年度的領(lǐng)域主席，國際數(shù)據(jù)挖掘大會（KDD）2012年度的展覽和演示主席，國際互聯(lián)網(wǎng)大會（WWW）2011年度的領(lǐng)域主席。他擔任美國計算機學會會刊《信息系統(tǒng)（TOIS）》的副主編，國際期刊《信息檢索》和《人工智能》的編委，和數(shù)十個國際期刊的審稿專家。他是包括WWW, SIGIR, ICML, ACL, ICIP等在內(nèi)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?qū)W習研討會(LR4IR)2007-2009年度的聯(lián)合主席(Co-chair)，和2010年排序?qū)W習競賽的聯(lián)合組織者。他曾經(jīng)在WWW、SIGIR、KDD等國際會議上做關(guān)于排序?qū)W習的主題講座(tutorial)，并受邀作為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(nèi)的十余所國內(nèi)外高校講授《排序?qū)W習》和《機器學習》的課程。
代表作
Internet Economics
● Joint Optimization of Bid and Budget Allocation in Sponsored Search,KDD2012
● Relational Click Prediction for Sponsored Search,WSDM2012.
● An Advertiser-Centric Approach to Understand User Click Behavior in Sponsored Search,CIKM2011.
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 withSIGIR 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 withSIGIR 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.