There are some papers collected HERE. You may want to select paper from them.

• 9/25 (Fri.) Scan presetns Chunking with Support Vector Machines.
• 10/2 (Fri.) Kai-Min presents Trust region Newton method for large-scale logistic regression
• 10/9 (Fri.) Chen-Tse presents his work
• 10/16 (Fri.) GuoXun present his work.
• 10/23 (Fri.) GuoXun present his work.
• 10/30 (Fri.) OMG present ???.
• 11/6 (Fri.) PoPo present Fast Logistic Regression for Text Categorization with Variable-Length N-grams.
• 11/13 (Fri.) Kai-Min present An Affine-Scaling Interior-Point Method For Continuous Knapsack Constraints.

We will have meeting on Friday afternoon at 524/526, starting from 3:20pm.

• 5/1 (Fri.) Scan presents the rest of SMO linear convergence.
• 5/8 (Fri.) Kai-Min presents Sparse Online Learning via Truncated Gradient.
• 5/14 (Thu.) Janet presetns her work “Maximum Entropy”.
• 5/21 (Thu.) Ho Chia-Hua presents A Dual Coordinate Descent Method for Large-scale Linear SVM
• 6/5 (Fri.) Kai-Min presents Yin-Wen's thesis.
• 5/29 (Thu.) Janet presents pipibjc's thesis.
• 6/4 (Thu.) Kai-Min presents Yin-Wen's thesis.
• 6/5 (Fri.) Chen-Tse,博瀚 presents eaudex's thesis.
• 6/12 (Fri.) Kai-Min presetns the rest of Sparse Online Learning via Truncated Gradient.
• 6/19 (Fri.) Tian-Liang presetns Learning to Classify with Missing and Corrupted Features .
• 6/26 (Fri.) pipibjc presetns LYin-Wen's thesis.
• 7/2 (Thu.) Tian-Liang presetns the rest of Learning to Classify with Missing and Corrupted Features .
• 7/9 (Thu.) Dino presents his research
• 7/10 (Fri.) Chia Hua presents An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression
• 7/16 (Thu.) Scan presetns Stochastic Methods for L1 Regularized Loss Minimization.
• 7/17 (Fri.) Chia Hua presents An Interior-Point Method for Large-Scale l1-Regularized Logistic Regression
• 7/23 (Thu.) 2nd-year master students presents their work
• 7/24 (Fri.) Others present their work
• 7/30 (Thu.) Chen-Tse 博瀚 presents svvd
• 8/6 (Thu.) Kai-Min presents A Note on Decomposition Methods for Support Vector Regression
• 8/7 (Fri.) Typhoon 莫拉克
• 8/13 (Thu.) Chia Hua presents arge Linear Classification when Data Cannot Fit in Memory
• 8/14 (Fri.) Tian-Liang presents Learning Linear Dynamical Systems without Sequence Information
• 8/21 (Fri.) Chen-Tse presents Tree Decomposition for Large-Scale Support Vector Machines
• 8/27 (Thu.) Scan presents Hash Kernels for Structured Data
• 8/28 (Fri.) Po-Han presents Feature Hashing for Large Scale Multitask Learning
• 9/3 (Thu.) Kai-Min presents Trust region Newton method for large-scale logistic regression
• 9/4 (Fri.) Tian-Liang presents
• 9/10 (Thu.) Chen-Tse presents Dual Augmented Lagrangian Method for Efficent Sparse Reconstruction
• 9/11 (Fri.) Po-Han presents Fast Solution of L1-morm Minimization Problems When the Solution May be Sparse
• ?? (??) ?? Bundle Methods for Regularized Risk Minimization.

We will have meeting on Monday afternoon at 524/526, starting from 3:00pm.

• 11/05(Mon.) Yin-Wen presents about structure svm.
• 10/29(Mon.) Yin-Wen presents about structure svm.
• 10/22(Mon.) No meeting today because of a speech.
• 10/15(Mon.) pipibjc presents about structure svm on LETOR.
• 10/08(Mon.) biconnect, rainfarmer present about their research.

We will have meeting on Friday morning at 524/526, starting from 10:00 am.

• 9/14(Fri.): GuoXun present about pegasos.
• 9/07(Fri.): GuoXun present “A Study on Threshold Selection for Multilable Classification”.
• 8/31(Fri.): everyone talk about their current research work.
• 8/24(Fri.): biconnect present about gaussian process regression.
• 8/24(Fri.): Bee present Chapter 3.
• 8/17(Fri.): canceled because of typhoon.
• 8/10(Fri.): Ma present about Image thumbnailing.
• 8/03(Fri.): Bee present Chapter 3.
• 8/03(Fri.): Rofu present paper.
• 7/27(Fri.): GuoXun present the rest part of Chapter 2.
• 7/27(Fri.): pipibjc present about LETOR.
• 7/20(Fri.): GuoXun present Chapter 2 of Numerical Optimization, from page 11 to page 22.
• 7/20(Fri.): greenoyster present about his research.
• 7/13(Fri.): Ma presents netflix challenge.

We will have meeting on Friday morning at 524, starting from 9:30.

• 6/8(Fri.): biconnect/rainfermer present hotterornotter
• 6/1(Fri.): rafan present his Master thesis
• 5/18(Fri.): GuoXun present sub-GrAdient SOlver for SVM
• 5/18(Fri.): acherub present comments on CVM
• 5/11(Fri.): acherub present CVM
• 5/4(Fri.): zao present Trust Region Newton Method for Large-Scale Regularized Logistic Regression
• 4/20(Fri.): oyster present Trust Region Newton Method for Large-Scale Regularized Logistic Regression
• 3/30(Fri.): pipibjc presents the python interface of libsvm
• 3/23(Fri.): Ma presents Statistical Edge Detection: Learning and Evaluating Edge Cues
• 3/16(Fri.): Ma presents Statistical Edge Detection: Learning and Evaluating Edge Cues
• 3/16(Fri.): GuoXun presents libsvm string code
• 3/09(Fri.): oyster presents Maximum-Gain Working Set Selection for SVMs
• 3/02(Fri.): oyster presents Maximum-Gain Working Set Selection for SVMs

We will have meeting on Tuesday and Friday starting from 13:00.

• 2/13(Tue.): zao presents Newton method
• 2/09(Fri.): zao presents Newton method
• 2/09(Fri.): pipibjc presents TrecVID tsinghua2004
• 2/06(Tue.): Ma presents Balanced Graph Matching
• 2/02(Fri.): biconnect and rainfarmer present their work
• 1/30(Tue.): zao presents On The Limited Memory BFGS Method For Large Scale Optimization
• 1/26(Fri.): rafan presents Fast Transpose methods for kernel learning on sparse data

We will have meeting on Friday afternoon at 524 this semester, starting from 12:30 PM.

• 01/05(Fri.): oyster presents about solving quadratic problems
• 12/29(Fri.): zao presents On The Limited Memory BFGS Method For Large Scale Optimization
• 12/22(Fri.): zao presents about training logistic regression
• 12/15(Fri.): oyster presents about solving quadratic problems
• 12/08(Fri.): oyster presents SimpleSVM
• 12/01(Fri.): oyster presents SimpleSVM
• 12/01(Fri.): rafan presents about multi-label
• 11/24(Fri.): rafan presents about multi-label
• 11/24(Fri.): eaglet presents about Support Vector Machines Solvers
• 11/17(Fri.): eaglet presents about Support Vector Machines Solvers
• 11/10(Fri.): eaglet presents about Support Vector Machines Solvers
• 11/03(Fri.): Ma presents chapter 3 of A Family of Algorithms for Approximate Bayesian Inference
• 10/27(Fri.): rafan presents The challenge problem for automated detection of 101 semantic concepts in multimedia.
• 10/20(Fri.): zao presents Bayesian Pattern Ranking for Move Prediction in the Game of Go
• 10/13(Fri.): rainfarmer presents Nonnegative Matrix Factorization and I-Divergence Alternating Minimization
• 10/6(Fri.): No Meeting for Moon Festival
• 9/29(Fri.): rainfarmer presents Nonnegative Matrix Factorization and I-Divergence Alternating Minimization

We will have meeting on Friday morning at 524 this summer, starting from 9:30 AM.

• 9/22(Fri.): biconnect presents about working set
• 9/15(Fri.): biconnect presents about working set
• 9/08(Fri.): Ma presents the EM tutorial
• 9/01(Fri.): janet presents ftp://ftp.research.microsoft.com/pub/tr/TR-2006-80.pdf TrueSkill: A Bayesian Skill Rating System
• 8/25(Fri.): biconnect presents about P-SVM
• 8/18(Fri.): rafan presents Statistical Debugging: Simultaneous Identification of Multiple Bugs
• 8/11(Fri.): oyster presents A study on thresholding strategies for text categorization
• 8/04(Fri.): biconnect presents Improving text categorization methods for event tracking
• 7/28(Fri.): rainfarmer presents Large Scale Image-Based Adult-Content Filtering
• 7/21(Fri.): zao presents An Introduction to Conditional Random Fields for Relational Learning
• 7/19(Wed.): Ma presents An evaluation of statistical approaches to text categorization
• 7/14(Fri.): zao presents An Introduction to Conditional Random Fields for Relational Learning
• 7/07(Fri.): Benyah presents his research work
• 7/05(Wed.): zao presents An Introduction to Conditional Random Fields for Relational Learning(pp7~)

We will have meeting on Friday morning at 524 this semester.

• 6/30(Fri.): zao presents An Introduction to Conditional Random Fields for Relational Learning
• 6/23(Fri.): No meeting today
• 6/16(Fri.): oyster presents RCV1: A New Benchmark Collection for Text Categorization Research
• 6/09(Fri.): No meeting today
• 6/02(Fri.): zao presents about acoustic interface
• 5/26(Fri.): pipibjc presents about image retrieval
• 5/26(Fri.): eaglet presents about video search
• 5/26(Fri.): rainfarmer presents about semi-supervised learning
• 5/26(Fri.): Ma presents about watermark
• 5/19(Fri.): Ma presents about watermark
• 5/19(Fri.): pipibjc presents about hierarchical classifier
• 5/19(Fri.): eaglet presents about imabalanced data
• 5/12(Fri.): eaglet presents about imabalanced data
• 5/12(Fri.): biconnect presents about document vector
• 5/05(Fri.): Ma presents about face
• 5/05(Fri.): rainfarmer presents about music
• 5/05(Fri.): pipibjc presents A Limited Memory Variable Metric Method in Subspaces and Bound Constrained Optimization Problems
• 4/28(Fri.): pipibjc presents A Limited Memory Variable Metric Method in Subspaces and Bound Constrained Optimization Problems
• 4/21(Fri.): No meeting today
• 4/14(Fri.): eaglet presents about computer chess
• 4/07(Fri.): Ma presents about EM
• 3/31(Fri.): somi presents about the project with video search
• 3/24(Fri.): bionnect presents about Gaussian Process
• 3/24(Fri.): rainfarmer presents the connection between two papers
• 3/17(Fri.): rainfarmer presents
• 3/10(Fri.): biconnect presents A Matching Pursuit Approach to Sparse Gaussian Process Regression
• 3/03(Fri.): Tzu-Kuo presents a chapter in “The method of paired comparisons”

We will have meeting at 524 on Monday and Friday afternoon during the vacation.

• 2/18(Fri.): Tzu-Kuo presents
• 2/13(Mon.): puffer presents
• 2/10(Fri.): puffer presents
• 2/06(Mon.): Tzu-Kuo presents

We will have meetings at 524 on Tuesday morning/Friday afternoon this semester.

• 1/27(Fri.): puffer presents Optimizing Search Engines Using Clickthrough Data
• 1/27(Fri.): rainfarmer presents about regularization
• 1/06(Fri.): Somi presents The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
• 1/06(Fri.): eaglet presents about SVR
• 1/03(Tue.): eaglet presents about SVR
• 12/30(Fri.): eaglet presents about SVR
• 12/30(Fri.): pipibjc presents
• 12/27(Tue.): rafan presents about making SVM faster
• 12/23(Fri.): rainfarmer presents about NMF
• 12/23(Fri.): rafan presents about making SVM faster
• 12/20(Tue.): rainfarmer presents about NMF
• 12/16(Fri.): rainfarmer presents about NMF
• 12/13(Tue.): rainfarmer presentsabout NMF
• 12/09(Fri.): Bjchen presents Subsystem Identification Through Dimensionality Reduction of Large-Scale Gene Expression Data, Sensitive pattern discovery with 'fuzzy' alignments of distantly related proteins
• 12/02(Fri.): Bjchen presents