Abstract Semiconductor is the foundation of modern embedded systems. In this high computation power era, the circuit probing value of semiconductor production is widely concerned. In this series of competition held by TSMC, we have more than 100,000 features by hand. Thus, the feature dimension reduction is a very key procedure for us. On top
Year: 2021
College Student Research Scholarship: Real-time classification with missing data given models
Abstract With the explosion amount of information caused by Internet expansion, machine learning is getting more and more popular recently. However, real world application of machine learning theory is still very challenging and hard to achieve. One of the main difficulties stops the direct application is the issue called data loss. No matter data loss
A Classification model for Diverse and Noisy Labelers
Abstract With the popularity of the Internet and crowdsourcing, it becomes easier to obtain labeled data for specific problems. Therefore, learning from data labeled by multiple annotators has become a common scenario these days. Since annotators have different expertise, labels acquired from them might not be perfectly accurate. This paper derives an optimization framework to
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Convex Optimization Final Project
We take one of the machine learning task from Kaggle, house price prediction, as the topic of this final project. One of the main reasons is that the provided dataset is relatively easy to parse and manipulate. It turns out that we have much time to do a thorough feature analysis for both numerical and
Convex Optimization Homework 4
In this homework, I am working on the relationships between primal problems and dual problems, which is derived by solving Lagrange Multiplier. Among textbook problems, there are two coding problems that need to be solved with cvx package in MATLAB. Experiment results and codes are attached in the report.
Convex Optimization Homework 3
The first part of this homework is problems extracted from textbook. They are mainly about log-concavity of Gaussian cumulative function, solving optimization problems with constraints, simplification of general optimization problems to specific quadratic problems, and generalized posynomials and geometric programming. Later on, for the second of the homework, I need to solve a predefined maximum
Convex Optimization Homework 2
For the first part of this homework, I am asked some questions about Kullback-Leibler divergence and the differentiation between convex, concave, quasiconvex, and quasi concave functions. For the second part, I need to derive the update for log-sum-exp formula and implement a simple function to simulate Least Action principle in Physics with cvx package in
Convex Optimization Homework 1
In the very first homework of this class, I first work on textbook problems, such as Voronoi sets and polyhedral decomposition, positive semidefinite cones, and properties of dual cones. Later, I am asked to find out the minimum polyhedron that can cover a sphere that is centered at (r, r, r) with radius r.
Operating System Quarter Project
In this quarter project, we are asked to do a detailed analysis for an operating system in different aspects. For CPU and scheduling, we need to estimate the overheads for procedure calls and system calls, task creation time, and context switch time. For memory, we have to calculate Random Access Memory (RAM) access time, RAM
Operating System Homework 3
For the last homework, I am asked about not only the motivation of using scheduler activations, but also some details about Log-Structured File System (LFS), including what the assumptions LFS have and how data reading, writing, and segment cleaning are done in LFS.
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