Differences

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--- presentations [2012/09/27 16:09] – hj
+++ presentations [2012/11/06 21:37] – hj
@@ Line 7: / Line 7: @@
   * Deep Neural Networks: {{:learning-deep-ai.pdf|paper3}} **(by Hong)**
-  * Feature Dimensionality Reduction: {{:dimred-chris.pdf|paper4}}
+  * Feature Dimensionality Reduction: {{:dimred-chris.pdf|paper4}} **(by Boze)**
-  * Conditional Random Field: {{:crf.pdf|paper5}} and {{:crf-jafferty2001.pdf|paper6}}
+  * Conditional Random Field: {{:crf.pdf|paper5}} and {{:crf-jafferty2001.pdf|paper6}} **(by Martin)**
   * Stochastic Gradient Descent: {{:bottou-mlss-2003.pdf|paper7}}, {{:bottou-onlinelearning-98.pdf|paper8}} and {{:nips2011_distributed_optimization.pdf|paper9}}  **(by Hengyue)**
-Each person makes a presentation (35-40 minutes) on one of the above topics and leaves 5 minutes for Q&A.
+Each person makes a presentation (35-40 minutes) on one of the above topics and leaves 5 minutes for Q&A. **The midterm presentation has been scheduled in a single 3-hr time slot from 11am-2pm at __LAS3033__ (not our regular classroom) on Oct 29 (Mon). As a result, the class on Oct 24 is cancelled.**
 **2. Final Presentation:**  (Please select your topic from the following list or let me know any other topic you may be interested in.)
+  * Discriminative Training of HMMs:  {{:jiang_dt_survey.pdf|paper10}} and {{:woodland_mmie.pdf|paper11}}
+  * Bayesian Learning of HMMs:  {{:gauvain_map.pdf|paper12}} and {{:huo_online.pdf|paper13}}
+  * Latent Semantic Analysis for Language Model:  {{:belleg_lsa.pdf|paper14}}
+  * Weighted Finite State Transducer Optimization for Speech and Language Processing:  {{:wfst-lvcsr.pdf|paper15}}
+  * SPAM filtering:  {{:spam-filtering.pdf|paper16}}
+  * Auto Summarization: {{:auto-summarization.pdf|paper17}}  **(by Martin)**
+  * Open-Domain Q&A: {{:ibm-ai-qna.pdf|paper18}}