All Posts

• Quantum 22
• Dimension 19
• Analysis 18
• ps 15
• Convex 12
• others 6
• Bayesian 6
• Advanced 5
• compbio 1

Quantum

[Quantum Data Science] Part 7. Quantum Factoring Algorithm using Schnorr’s algorithm.

3 minute read

Algorithm for factoring large integer.

[Quantum Data Science] Part 6. Quantum Algorithm for Combinatorial Optimization

12 minute read

Algorithm for finding optima of combinatorial problems

[Quantum Data Science] Part 5. Quantum Algorithm for Finance

10 minute read

Algorithm for calculating financial portfolio

[Quantum Data Science] Part 4. Quantum Kernel Space

7 minute read

Quantum feature space using quantum kernel

[Quantum Data Science] Part 3. Parameterized Quantum Circuit

6 minute read

Parameterized Quantum Circuit and their optimization method

[Quantum Data Science] Part 2. Quantum Information Encoding

5 minute read

Encoding method to embed data into quantum states

[Quantum Data Science] Part 1. Introduction to Quantum Theory

7 minute read

Basic Terminology used at the Quantum Theory

[Basic of Quantum Computer] Part 7. Security System of the Quantum computer and Quantum Protocol

8 minute read

Comparing security of quantum and classical computer and Quantum protocol

[Basic of Quantum Computer] Part 6. Starting Qiskit

3 minute read

Installing qiskit and constructing basic circuit Qiskit

[Basic of Quantum Computer] Part 4. Grover’s Algorithm, Deutsch’s Algorithm

10 minute read

Oracle, Amplitude Amplification, Grover’s and Deutsch’s Algorithm

[Basic of Quantum Computer] Part 3.Complex Number and Quantum Fourier Transformation

8 minute read

Basic concept of the complex number and its usage in the quantum computer]

[Basic of Quantum Computer] Part 2.Quantum Gate and Basic Circuit

8 minute read

basic component of the quantum computer.

[Basic of Quantum Computer ]Part 1.Concept of Quantum Computer and Qubit

11 minute read

Introduction and fundamentals of Quantum computer

[양자 데이터 사이언스] Quantum Approximated Optimization Algorithm

5 minute read

수정예정(오류있음)

[양자 데이터 사이언스] HHL Algorithm과 Hybrid HHL Algorithm

5 minute read

양자컴퓨터를 이용한 행렬 계산법

[양자컴퓨터 기초 이론] 7. RSA 보안체계와 양자 프로토콜

7 minute read

소인수 분해를 기반으로한 현세대 암호이론 기초와 양자컴퓨터의 암호이론 기초

[양자컴퓨터 기초 이론] 6. 키스킷 시작하기

2 minute read

Qiskit 설치 및 기본적인 회로작성

[양자컴퓨터 기초 이론] 5. 그로버 알고리즘과 도이치 알고리즘

8 minute read

오라클, 확률증폭, Grover’s Algorithm과 Deutsch’s Algorithm

[양자컴퓨터 기초 이론] 4. 양자 페이즈 추정과 내적 계산법

6 minute read

Quantum Phase Estimation와 Quantum State Distance Measure

[양자컴퓨터 기초 이론] 3.복소수의 기본과 푸리에 변환

5 minute read

복소수에 대한 기본적인 개념과 Quantum Fourier Analysis

[양자컴퓨터 기초 이론] 2.양자 게이트와 회로

10 minute read

양자 게이트와 이를 이용한 기본적인 회로들

[양자 컴퓨터 기초 이론] 1.양자컴퓨터와 큐빗

9 minute read

양자 컴퓨터 인트로 및 fundamentals

Back to top ↑

Dimension

[Paper Review] Dimensionality Reduction as Probabilistic Inference

6 minute read

Probabilistic Framework to interpret non-probabilistic Algorithms

[Paper Review] Dimensionality Reduction as Probabilistic Inference

2 minute read

Probabilistic Framework to interpret non-probabilistic Algorithms

[Paper Review] Sparse Sufficient Dimension Reduction

5 minute read

Sparse Sufficient Dimension Reduction using Penalty

[Experiment] Non-linear Sufficient Dimension Reduction using quantum kernel

2 minute read

plans to build dimension reduction of quantum version

[Paper Review] Sufficient Dimension Folding for Tensorial Data

6 minute read

Sufficient Dimension Folding Theory and Techniques to reduce the dimension of tensorial data.

[Sufficient Dimension Reduction] Part 4. Central Mean Space

3 minute read

Generalized version of SDR and SIR

[Non-linear Dimension Reduction] Part 3. Central sigma-Field for Nonlinear SDR and GSIR

7 minute read

Generalized version of SDR and SIR

[Non-linear Dimension Reduction] Part 2. Coordinate Representation and KPCA

7 minute read

Non-linear Dimension Reduction - 2. Coordinate Representation and KPCA

[Non-linear Dimension Reduction] Part 1. Reproducing Kernel Hilbert Space

8 minute read

Reproducing Kernel Hilbert Space

[Sufficient Dimension Reduction] Part3. Contour Regression and Directional Regression

8 minute read

Contour regression and Directional Regression

[Sufficient Dimension Reduction] Part2. Advanced algorithm of SIR

9 minute read

Parametric, Kernel Inverse regression, Sliced Average Variance Estimator.

[Sufficient Dimension Reduction] Part1. Introduction and Sliced Inverse Regression

9 minute read

Introduction to SDR and SIR method

[Basic Dimension Reduction] Part4. Advanced PCA

2 minute read

PCA의 응용 기법에 대한 설명

[Basic Dimension Reduction] Kernel Trick을 활용한 알고리즘 (Polynomial Regression,Kernel PCA,SVM)

6 minute read

Kernel Trick을 활용한 High-Dimension Mapping Computing의 간소화

[Basic Dimension Reduction] Part3. Independent Components Analysis

7 minute read

ICA에 대한 설명

[Basic Dimension Reduction] Part2. Non Negative Matrix Factorization

6 minute read

NMF 최적화에 대한 설명

[Basic Dimension Reduction] Part1. Bregman Divergence

3 minute read

Bregman Divergence에 관한 설명

[Basic Dimension Reduction] 군집분석(Cluster Analysis)

4 minute read

분할기법,계층기법,밀도기법에 대한 설명

[Basic Dimension Reduction] PCA,MCA,FA를 활용한 차원축소

4 minute read

PCA,MCA,FA에 대한 대략적인 설명

Back to top ↑

Analysis

[Real Analysis] Ch4. Hilbert Space

9 minute read

Hilbert Space

[Real Analysis] Ch3. Differentiation and Integration

11 minute read

Differentiation

[Real Analysis] Ch2. Integration Theory

7 minute read

Integration Theory

[Real Analysis] Ch1. Measure Theory

18 minute read

Measure Theory

[Hilbert Space] Introduction to Function Space

11 minute read

Exploring function space with Hilbert Space Framwork

[Hilbert Space] Linear Operator in Euclidean Space

8 minute read

Advanced concept about Matrix

[RCA] Ch2.Positive Lebesgue measure(2/2)

14 minute read

Positive Lebesgue Measure

[RCA] Ch2.Positive Lebesgue measure(1/2)

16 minute read

Riesz representation theorem

[RCA] Ch1.Abstract Integration (2/2)

10 minute read

Absatract Integration , lebesgue integration, measure zero

[RCA] Ch1.Abstract Integration (1/2)

11 minute read

Absatract Integration, sigma-algebra, simple function, measure

[Marsden_Analysis] 4. Continuous Mapping - Part A(KOR)

6 minute read

Continuous Function

[Marsden_Analysis] 4. Continuous Mapping - Part A (KOR)

6 minute read

Continuous Function

[Marsden_Analysis] 3. Compact and Connected Set - Part B (KOR)

5 minute read

Nested Set Property,Connected Set

[Marsden_Analysis] 3. Compact and Connected Set - Part A (KOR)

12 minute read

Compacctness

[Marsden_Analysis] 2. The Topology of Euclidean Space - Part B(KOR)

8 minute read

Boundary Point, Sequence and Completness

[Marsden_Analysis] 2. The Topology of Euclidean Space - Part A (KOR)

9 minute read

Set Theory, Open Set, Closed Set

[Marsden_Analysis] 1.The Real Line And Euclidean Space - Part B (KOR)

11 minute read

Least Upper Bounds와 Cauchy Sequence, Cluster Point

[Marsden_Analysis] 1.The Real Line And Euclidean Space - Part A (KOR)

6 minute read

Ordered Field,Number System, Real Number

Back to top ↑

ps

계속 쓰는 시

6 minute read

계속 쓰는 시

6월의 시

2 minute read

6월에 적은 시

4월의 시

less than 1 minute read

4월에 적은 시

3월의 시

1 minute read

3월에 적은 시

20대의 마침표.

3 minute read

연작시

2월의 시

less than 1 minute read

2월에 적은 시

1월의 시

1 minute read

1월에 적은 시

12월의 시

1 minute read

12월에 적은 시

11월의 시

less than 1 minute read

11월에 적은 시

10월의 시

2 minute read

10월에 적은 시

9월의 시

less than 1 minute read

9월에 적은 시

8월의 시

1 minute read

8월에 적은 시

7월의 시

2 minute read

7월에 적은 시

6월의 시

1 minute read

6월에 적은 시

5월의 시

1 minute read

5월에 적은 시

Back to top ↑

Convex

[Second-Order Method] Part4 - Quasi Newton Method.

3 minute read

Quasi Newton’s Method to accelerate learning.

[Second-Order Method] Part3 - Primal-Dual Interior-Point Methods

4 minute read

Solving convex problem with inequality constraints

[Second-Order Method] Part2 - Barrier Method

4 minute read

Solving convex problem with inequality constraints

[Second-Order Method] Part1 - Newton Raphson Method

5 minute read

Newton Raphson Method

[Theory of Optimization] Convex Optimization의 최적화 기법 총정리

9 minute read

Gradient Descent와 Newtown’s Method의 정리

[First-Order Method] Part3. Proximal Gradient Descent

6 minute read

Proximal Gradient Descent and Stochastic Gradient Descent

[First-Order Method] Part2. Subgradient Method

9 minute read

Subgradient Method

[First-Order Method] Example2. Subgradient method

8 minute read

L1 penalty에 대한 subgradient method 실습

[First-Order Method] Part1. Gradient Descent

5 minute read

Gradient Descent

[First-Order Method] Example1. Basic Gradient Descent

11 minute read

OLS에 대한 Gradient Descent 실습

[Theory of Optimization] Application of Duality

6 minute read

Application of Duality

[Theory of Optimization] convexity and duality

10 minute read

meaning of convex and duality

Back to top ↑

others

KQC 2022년 여름 인턴 모집 안내

less than 1 minute read

Korea Quantum Computing

[생성모델] Basic Generative Model Part2 - Regulized AutoEncoder

5 minute read

Sparse Autoencoder, Denoising AutoEncoder, Contractive Autoencoderㅇ

[생성모델] Basic Generative Model Part1 - Basic Preview of Generative Model and AutoEncoder

5 minute read

생성모델의 개념과 Basic Autoencoder

[기술]마크다운 사용하기

2 minute read

마크다운 매뉴얼에 대한 서술

[기술]주피터 노트북으로 슬라이드쇼 만들기

3 minute read

nbconvert,rise,reveal.js에 대한 설명

[프로젝트]IGA Works 클릭율 예측 대회 참가 기록

4 minute read

예측 모델링 과정과 개선점에 대한 포스팅

Back to top ↑

Bayesian

[Bayesian Inference]히든 마르코프 체인

3 minute read

기본적인 히든 마르코프 체인 구조에 대한 서술

[Bayesian Inference] Finite Mixture Model 실습

5 minute read

Finite Mixture Model를 이해하고 구현해보기

[Bayesian Inference] VI 공식 적용 및 실습

6 minute read

VI를 통해 다중 회귀분석 적용해보기

[Bayesian Inference] Markov Chain Monete Carlo

2 minute read

MCMC방법인 Gibbs Sampling과 MH 기법에 대한 정리

[Bayesian Inference] GMM 모수 추정 실습

6 minute read

GMM의 모수를 Gibbs Sampler와 EM Algorithm으로 추정해보기

[Bayesian Inference] Variational Inference

5 minute read

PCA,MCA,FA에 대한 대략적인 설명

Back to top ↑

Advanced

[Spatial Interpolation Theory] Ch 2. Properties of Random Fields

1 minute read

Preliminary about linear prediction

[Spatial Interpolation Theory] Ch 1. Linear Prediction

2 minute read

Preliminary about linear prediction

[Envelopes Theory] Ch 1. Response Envelopes

8 minute read

Preliminary about Vector Space, Multivariate Linear Model and Response Envelopes

[Random Matrix Theory] Ch2. Stirling’s Formula and Eigenvalue Theory

12 minute read

Stirling’s formula about approximate behavior of permutation and various eigenvalue inequality and equality.

[Random Matrix Theory] Ch1. Probability Theory

18 minute read

Preliminary of random matrix theory.

Back to top ↑

compbio

[Paper Review] Finemapping for GWAS

less than 1 minute read

Finemapping for GWAS Variant

Back to top ↑