Machine Learning and Data Analysis (Strijov's practice)/Group 174, spring 2014

Материал из MachineLearning.

Основная статья: Machine Learning and Data Analysis (Strijov's practice)

My first research paper

The course involves Experts, Assistants and Sutudents of the Moscow Institute of Physucs and Technology.

Course description
Short URL http://goo.gl/Kl1dEG

Format

A student is willing to learn to formally state research problems, find adequate references, generate novel and significant ideas for problem solving.

An assistant helps the student with technical issues, consults the student on machine learning topics, promptly reacts to arising problems, performs evaluations and grading. Each advisor is supposed to possess sufficient publishing experience. Ideally, the assistant is writing paper on the adjacent topic. It is recommended to organize weekly reviewing process in such way that a student would input the corrections himself/herself.

An expert guarantees novelty and importance of the paper, suggests the problems, provides data.

Results

Author	Research title	Link	Assistant	HW-1,2	Code	Score	Grade
Gazizullina Rimma	Capacity of railway cargo transportation forecasting	[1], pdf	Stenina Maria	$\frac{15}{15}+\frac{10}{16}$	[MF]TAI+L+SBR+CV+T>DEH(J)	16	10
Grinchul Andrey	Struture Learning	[2], pdf	Varfolomeeva Anna	$\frac{7}{15}+\frac{2}{16}$	[F]TA+I+LSBR+СV+T+D+E(F)	14,5	9
Guschin Alexander	Inductive model geneneration in information retrieval	[3], pdf	Kuznetsov Mikhail	$\frac{5}{15}+\frac{2}{16}$	[F]TAI+L+SBRCVTDEHS(F)	15,5	9
Efimova Irina	Differential diagnosis (ECG)	[4], pdf	Celyh Vlada	$\frac{15}{15}+\frac{12}{16}$	[MF]T+A+I+L+SB++R+CV+TDE+H(J ed)	17,25	10
Zhukov Andrey	Robust university ranking	[5], pdf	Kuznetsov Mikhail	$\frac{8}{15}+0$	[F]TAIL+SBRCVTDEHS(F)	15,25	9
Ignatov Andrey	MAbifold learning for quasiperiodic time series forecasting	[6], pdf	Ivkin Nkita	$0+\frac{7}{16}$	[MF]TA+I+L+S+B+R+C+VTD>E+HS (J if ed)	18	10
Karasikov Mikhail	Dimensionality reduction for multi-class learning problems reduced to multiple binary problems	[7], pdf	Yu.V. Maximov	$0+0$	[MF]TAI+L+SBRC+V+TDESH(J)	15	10
Kulunchakov Andrey	Detection of isomorphic structures in essentially nonlinear regression models	[8], pdf	Sologub Roman, Kuznetsov Mikhail	$\frac{10}{15}+\frac{14}{16}$	[F]T+AI+L+S+BR+CVT++D+EHS(J ed-ed)	17	10
Lipatova Anna	Simultaneous Clustering Of A Set Of Time Series And Corresponding Forecasting Models	[9], pdf	Motrenko Anastasia	$\frac{8}{15}+\frac{6}{16}$	[MF]TA+I+LSBR-CVTDE (J when ed)	14,25	10
Makarova Anastasia	Nonlinear forecasting	[10], pdf	Motrenko Anastasia	$0+0$	[F]TAI-LSB+R-CVTD>E>(F)	12,75	9
Plavin Alexander	Number of topics optimization in probabilistic topic models by sparsing regularizer	[11], pdf	Potapenko Anna	$\frac{13}{15}+\frac{14}{16}$	[F]T+A+I+L+S+BR++CVTD+>>(?)	14	10
Popova Maria	Selection of optimal physical activity classification model using measurements of accelerometer	[12], pdf	Tokmakova Alexandra	$\frac{11}{15}+\frac{6}{16}$	[MF]T+AI+L++SB++R+CV+TD+(JV ed)	15,25	10
Shvets Mikhail	Multimodel interpretation foe sociologic data	[13], pdf	Aduenko Alexander	$\frac{11}{15}+\frac{4}{16}$	[M+F]T+A+I+L+S+B+R+CVTD+E(F)	16,25	9
Shinkevich Mikhail	On regularization and model robustenss	[14], pdf	Dudarenko Marina	$\frac{15}{15}+\frac{9}{16}$	[MF]T+AIL+S+BR+CV+T+D+E+H(J ed)	17	10