The goal of the workshop is to circumvent the exhaustive method of building programs from scratch for every machine learning task at hand, through knowledge of applicable existing tools in statistics and mathematics. The workshop integrates knowledge from probability, statistics, linear algebra, and optimization required for machine learning tasks of pattern analysis and modelling. The idea is to focus on the current research studies, challenges, and practical experiences in the domain of machine learning, and trying to deal with them from mathematical and statistical perspectives.
09:00 - 10:15 |
10:00 - 11:30 |
12:00 - 13:00 |
Registration |
EM Algorithms and Its Applications in Machine Learning |
Alternating Direction Method of Multipliers |
10:15 - 10:45 |
11:30 - 11:45 |
13:00 - 14:30 |
Inauguration |
Tea Break |
Lunch |
10:45 - 12:15 |
11:45 - 12:45 |
14:30 - 16:00 |
EM Algorithms and Its Applications in Machine Learning |
Alternating Direction Method of Multipliers |
|
12:15 - 12:30 |
12:45 - 14:15 |
16:00 - 16:15 |
Tea Break |
Lunch Break |
Tea Break |
12:30 - 13:30 |
14:15 - 15:15 |
16:15 - 16:45 |
Probablity Related to Machine Learning |
Method of Least Squares and Statistical Regression |
Valedictory |
13:30 - 14:45 |
15:15 - 15:30 |
|
Lunch Break |
Tea Break |
|
14:45 - 15:45 |
15:30 - 17:00 |
|
Method of Least Squares and Statistical Regression |
||
15:45 - 16:00 |
||
Tea Break |
||
16:00 - 17:30 |
||
Probablity Related to Machine Learning |
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