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\noindent\textbf{Instructors}:\\ | ||
Javier Duarte, \href{mailto:[email protected]}{[email protected]}, OH M 11:00a--12:00p, MYR-A 5513\\ | ||
Aobo Li, \href{mailto:[email protected]}{[email protected]}, OH TBD\\ | ||
\noindent \textbf{Teaching assistant}: Anthony Aportela, \href{mailto:[email protected]}{[email protected]}, OH TBD\\ | ||
Aobo Li, \href{mailto:[email protected]}{[email protected]}, OH W 1:00--2:00p, MYR-A 4571\\ | ||
\noindent \textbf{Teaching assistant}: Anthony Aportela, \href{mailto:[email protected]}{[email protected]}, OH F 11:00a--12:00p, MYR-A 5516\\ | ||
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\noindent\textbf{Course webpage, Zoom link to lectures}:\\ | ||
\hspace*{1cm}Canvas: \href{https://canvas.ucsd.edu/courses/56257}{https://canvas.ucsd.edu/courses/56257}\\ | ||
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\noindent\textbf{Week 2} | ||
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\emph{Monday 4/8 (Duarte)}: \underline{Lecture 04}: Support vector machine, regularization, logistic regression | ||
\emph{Monday 4/8 (Duarte)}: \underline{Lecture 04}: Support vector machine | ||
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\emph{Wednesday 4/10 (Duarte)}: \underline{Lecture 05}: (Boosted) decision trees | ||
\emph{Wednesday 4/10 (Duarte)}: \underline{Lecture 05}: Regularization, logistic regression | ||
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\emph{Friday 4/12 (Duarte)}: Homework 1 due; \underline{Lecture 06}: (Boosted) decision trees (cont.); \underline{Hands-on}: Scikit-learn, XGBoost, classifying Higgs boson events | ||
\emph{Friday 4/12 (Duarte)}: Homework 1 due; \underline{Lecture 06}: (Boosted) decision trees | ||
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\noindent\textbf{Week 3} | ||
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\emph{Monday 4/15 (Li)}: \underline{Lecture 07}: (Deep) neural networks, backpropagation | ||
\emph{Monday 4/15 (Li/Duarte)}: \underline{Lecture 07}: (Boosted) decision trees (cont.); \underline{Hands-on}: Scikit-learn, XGBoost, classifying Higgs boson events | ||
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\emph{Wednesday 4/17 (Li)}: Homework 1 (corrections) due; Homework 2 released; \underline{Lecture 08}: (Deep) neural networks (cont.), training issue, data standardization | ||
\emph{Wednesday 4/17 (Li)}: Homework 1 (corrections) due; Homework 2 released; \underline{Lecture 08}: (Deep) neural networks, backpropagation | ||
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\emph{Friday 4/19 (Duarte)}: \underline{Lecture 09}: Optimizers: (Nesterov) momentum, RMSProp, Adam, skip connections, regularization: dropout, early stopping, \underline{Hands-on}: Keras, classifying jets with high-level features | ||
\emph{Friday 4/19 (Li)}: \underline{Lecture 09}: Classification metrics, confusion matrix, ROC curve, AUC | ||
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\noindent\textbf{Week 4} | ||
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\emph{Monday 4/22 (Duarte)}: \underline{Lecture 10}: Types of data, inductive bias, image-like data, convolutional neural networks | ||
\emph{Monday 4/22 (Duarte)}: \underline{Lecture 10}: (Deep) neural networks (cont.), training issue, data standardization; \underline{Hands-on}: Keras, classifying jets with high-level features | ||
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\emph{Wednesday 4/24 (Duarte)}: \underline{Lecture 11}: Convolutional neural networks (cont.) | ||
\emph{Wednesday 4/24 (Duarte)}: \underline{Lecture 11}: Optimizers: (Nesterov) momentum, RMSProp, Adam, skip connections, regularization: dropout, early stopping | ||
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\emph{Friday 4/26 (Li)}: Homework 2 due; \underline{Lecture 12}: Spherical convolutional neural networks, \underline{Hands-on}: Keras, classifying astronomical data (images) | ||
\emph{Friday 4/26 (Li)}: Homework 2 due; \underline{Lecture 12}: Types of data, inductive bias, image-like data, convolutional neural networks | ||
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\noindent\textbf{Week 5} | ||
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\emph{Monday 4/29 (Li)}: \underline{Lecture 13}: Time-series data, recurrent neural networks | ||
\emph{Monday 4/29 (Li)}: \underline{Lecture 13}: Convolutional neural networks (cont.) | ||
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\emph{Wednesday 5/1 (Li)}: Homework 2 (corrections) due; Homework 3 released; \underline{Lecture 14}: Recurrent neural networks (cont.) | ||
\emph{Wednesday 5/1 (Li)}: Homework 2 (corrections) due; Homework 3 released; \underline{Lecture 14}: Spherical convolutional neural networks | ||
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\emph{Friday 5/3 (Li)}: \underline{Lecture 15}: Recurrent neural networks (cont.); \underline{Hands-on}: Identifying radio signals (time series) | ||
\emph{Friday 5/3 (Duarte)}: \underline{Hands-on}: Keras, classifying astronomical data (images) | ||
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\noindent\textbf{Week 6} | ||
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\emph{Monday 5/6 (Duarte)}: \underline{Lecture 16}: Point cloud and graph-like data, relational inductive bias, permutation invariance/equivariance, graph neural networks | ||
\emph{Monday 5/6 (Li)}: \underline{Lecture 15}: Time-series data, recurrent neural networks | ||
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\emph{Wednesday 5/8 (Duarte)}: \underline{Lecture 17}: Graph neural networks (cont.) | ||
\emph{Wednesday 5/8 (Li)}: \underline{Lecture 16}: Recurrent neural networks (cont.) | ||
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\emph{Friday 5/10 (Duarte)}: Homework 3 due; \underline{Lecture 18}: Graph neural networks (cont.), \underline{Hands-on}: Spektral, $N$-body simulations, springs | ||
\emph{Friday 5/10 (Li)}: Homework 3 due; \underline{Hands-on}: Identifying radio signals (time series) | ||
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\noindent\textbf{Week 7} | ||
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\emph{Monday 5/13 (Li)}: \underline{Lecture 19}: Unsupervised learning, clustering | ||
\emph{Monday 5/13 (Duarte)}: \underline{Lecture 18}: Point cloud and graph-like data, relational inductive bias, permutation invariance/equivariance, graph neural networks | ||
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\emph{Wednesday 5/15 (Li)}: Homework 3 (corrections) due; Homework 4 released; \underline{Lecture 20}: Autoencoders | ||
\emph{Wednesday 5/15 (Duarte)}: Homework 3 (corrections) due; \underline{Lecture 19}: Graph neural networks (cont.) | ||
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\emph{Friday 5/17 (Li)}: Project proposal due; \underline{Lecture 21}: Variational autoencoders, \underline{Hands-on}: Finding anomalies in LHC/LIGO data | ||
\emph{Friday 5/17 (Duarte)}: Project proposal due; \underline{Hands-on}: Spektral, $N$-body simulations, springs | ||
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\noindent\textbf{Week 8} | ||
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\emph{Monday 5/20 (Duarte)}: \underline{Lecture 22}: Model compression, pruning | ||
\emph{Monday 5/20 (Li)}: \underline{Lecture 21}: Unsupervised learning, clustering | ||
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\emph{Wednesday 5/22 (Duarte, remote)}: \underline{Lecture 23}: Quantization | ||
\emph{Wednesday 5/22 (Li)}: \underline{Lecture 22}: Autoencoders, variational autoencoders | ||
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\emph{Friday 5/24 (Duarte)}: Homework 4 due; \underline{Lecture 24}: Knowledge distillation, \underline{Hands-on}: TensorFlow Model Optimization, QKeras | ||
\emph{Friday 5/24 (Li)}: Homework 4 due; \underline{Lecture 23}: \underline{Hands-on}: Finding anomalies in LHC/LIGO data | ||
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\noindent\textbf{Week 9} | ||
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\emph{Wednesday 5/29 (Guest)}: Homework 4 (corrections) due; \underline{Guest lecture}: TBD | ||
\emph{Wednesday 5/29 (Duarte)}: \underline{Lecture 24}: Model compression, pruning | ||
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\emph{Friday 5/31 (Guest)}: \underline{Guest lecture}: TBD | ||
\emph{Friday 5/31 (Duarte)}: \underline{Lecture 25}: Quantization | ||
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\noindent\textbf{Week 10} | ||
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\emph{Monday 6/3 (Guest)}: \underline{Guest lecture}: TBD | ||
\emph{Monday 6/3 (Duarte)}: Knowledge distillation | ||
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\emph{Wednesday 6/5 (Guest)}: \underline{Guest lecture}: TBD | ||
\emph{Wednesday 6/5 (Duarte)}: \underline{Hands-on}: TensorFlow Model Optimization, QKeras | ||
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\emph{Wednesday 6/7 (Guest)}: \underline{Guest lecture}: TBD | ||
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