ReleaseNotes: Fix matrix operations + other details

ReleaseNotes.txt

@@ -8,38 +8,48 @@ A complete list of changes for each release can be obtained by viewing the git
 commit history located at https://github.com/madlib/madlib/commits/master.
 
 Current list of bugs and issues can be found at http://jira.madlib.net.
+
 --------------------------------------------------------------------------------
 MADlib v1.8
 
 Release Date: 2015-July-17
 
 New features:
-* Latent Dirichlet Allocation (LDA) Performance Improvement
-    - Function lda_train() is 1.5X ~ 3X faster
-    - Improve the scalability support (vocabulary size multiplied by the
-      number of topics up to 250 million)
-* Matrix Operations
-    -
+* Improved Latent Dirichlet Allocation (LDA) Performance
+    - Function lda_train() is about twice as fast.
+    - Improved the scalability of the function
+      (vocabulary size x number of topics can be up to 250 million).
+* New module: Matrix operations
+    Added the following operations/functions for dense and sparse matrices:
+    - Mathematical operations: addition, subtraction, multiplication,
+      element-wise multiplication, scalar and vector multiplication.
+    - Aggregation operations: apply various operations including
+      max, min, sum, mean along a specified dimension.
+    - Visitor methods: extract row/column from matrix.
+    - Representation: convert a matrix to either dense or sparse representation.
 * Quotation and International Character Support
     - Most modules now support table and column names that are quoted and
       contain international characters, including:
         - Regression models (GLMs, linear regression, elastic net, etc.)
         - Decision trees and random forests
         - Unsupervised learning models (association rules, k-means, LDA, etc.)
-        - Summary, Pearson's correlation, and principal component analysis
+        - Summary, Pearson's correlation, and PCA
 * Array Norms and Distances
     - Generic p-norm distance
     - Jaccard distance
     - Cosine similarity
+* Text Analysis:
+    - Text utility for term frequency and vacabulary construction (prepares
+      documents for input to LDA).
 * Miscellaneous
-    - Text utility for term frequency and vacabulary construction
-    - Low-rank matrix factorization: 32-bit integer aupport (MADLIB-903)
-    - Cross-validation: classification support (MADLIB-908)
-    - Clean up functions for junk tables
+    - Improved organization of User and Developer guide at doc.madlib.net/latest.
+    - Low-rank matrix factorization: added 32-bit integer aupport (MADLIB-903).
+    - Cross-validation: added classification support (MADLIB-908).
+    - Added a new clean-up function for removing MADlib temporary tables.
 
 Note:
 - LDA models that are trained using MADlib v1.7.1 or earlier need to be
-  re-trained for the use of MADlib v1.8
+  re-trained to be used in MADlib v1.8.
 
 Known issues:
 - Performance for decision tree with cross-validation is poor on a HAWQ