[백준] 4796 : 캠핑 (Python)
백준
Posts by Tag
- 백준 12
- Python 12
- Review 11
- Quantization 11
- 경량화 9
- Knowledge Distillation 6
- Deep Learning 4
- NLP 4
- 밑시딥 4
- Machine Learning 2
- Model Compression 2
- Weight Averaging 2
- Blog 1
- VAE 1
- AutoEncoder 1
- Optimizer 1
- Pandas 1
- Anomaly Detection 1
- LLM 1
백준
Python
Review
[Review] Data-Free Quantization via Pseudo-label Filtering, CVPR, 2024
Zero Shot Quantization
[Review] GENIE: Show Me the Data for Quantization, CVPR, 2023
Zero Shot Quantization
[Review] Similarity of Neural Architectures using Adversarial Attack Transferability, ECCV, 2024
Model Similarity
[Review] Anomaly Score: Evaluating Generative Models and Individual Generated Images based on Complexity and Vulnerability, CVPR, 2024
Evaluation metric for generative models
[Review] SQWA: Stochastic QuantizedWeight Averaging for Improving the Generalization Capability of Low-Precision Deep Neural Networks, ICASSP, 2021
Stocahstic Weight Averaging
[Review] Averaging Weights Leads to Wider Optima and Better Generalization, IJAI, 2018
Stocahstic Weight Averaging
[Review] Improved Feature Distillation via Projector Ensemble, NeurIPS, 2022
FC Layer Ensemble을 이용한 Feature based KD
[Review] Anomaly Detection via Reverse Distillation from One-Class Embedding, CVPR, 2022
Knowledge Distillation을 이용한 Anomaly detection
[Review] Rethinking Soft Labels For Knowledge Distillation: A Bias-Variance Tradeoff Perspective, ICLR, 2021
Variance와 Bias 관점에서의 Knowledge Distillation
[Review] Distilling the Knowledge in a Neural Network, NIPS, 2014
Knowledge Distillation 분야의 시작
Quantization
[Review] Data-Free Quantization via Pseudo-label Filtering, CVPR, 2024
Zero Shot Quantization
[Review] GENIE: Show Me the Data for Quantization, CVPR, 2023
Zero Shot Quantization
[Review] Non-Uniform Step Size Quantization for Accurate Post-Training Quantization, ECCV, 2022
Non-uniform quantization
[Review] SQWA: Stochastic QuantizedWeight Averaging for Improving the Generalization Capability of Low-Precision Deep Neural Networks, ICASSP, 2021
Stocahstic Weight Averaging
[Review] Successive Log Quantization for Cost-Efficient Neural Networks Using Stochastic Computing, DAC, 2019
Successiv Log Quantization
[Review] FLightNNs: Lightweight Quantized Deep Neural Networks for Fast and Accurate Inference, DAC, 2019
Successiv Log Quantization
[Review] ADDITIVE POWERS-OF-TWO QUANTIZATION: AN EFFICIENT NON-UNIFORM DISCRETIZATION FOR NEURAL NETWORKS, ICLR, 2020
Non-uniform base-2 logarithmic quantization
[Review] INCREMENTAL NETWORK QUANTIZATION: TOWARDS LOSSLESS CNNS WITH LOW-PRECISION WEIGHTS, ICLR, 2017
Non-uniform base-2 logarithmic quantization
[Review] Convolutional Neural Networks using Logarithmic Data Representation, arxiv, 2016
Non-uniform base-2 logarithmic quantization
Basic Quantization Concepts
Quantization 기본 컨셉 정리
Fixed vs Floating point
소수점 표현 방식
경량화
[Review] Non-Uniform Step Size Quantization for Accurate Post-Training Quantization, ECCV, 2022
Non-uniform quantization
[Review] Successive Log Quantization for Cost-Efficient Neural Networks Using Stochastic Computing, DAC, 2019
Successiv Log Quantization
[Review] FLightNNs: Lightweight Quantized Deep Neural Networks for Fast and Accurate Inference, DAC, 2019
Successiv Log Quantization
[Review] ADDITIVE POWERS-OF-TWO QUANTIZATION: AN EFFICIENT NON-UNIFORM DISCRETIZATION FOR NEURAL NETWORKS, ICLR, 2020
Non-uniform base-2 logarithmic quantization
[Review] INCREMENTAL NETWORK QUANTIZATION: TOWARDS LOSSLESS CNNS WITH LOW-PRECISION WEIGHTS, ICLR, 2017
Non-uniform base-2 logarithmic quantization
[Review] Convolutional Neural Networks using Logarithmic Data Representation, arxiv, 2016
Non-uniform base-2 logarithmic quantization
[Review] MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases, ICML, 2024
Sub-billion scale LLM
[Review] Rethinking Soft Labels For Knowledge Distillation: A Bias-Variance Tradeoff Perspective, ICLR, 2021
Variance와 Bias 관점에서의 Knowledge Distillation
[Review] Distilling the Knowledge in a Neural Network, NIPS, 2014
Knowledge Distillation 분야의 시작
Knowledge Distillation
[Review] Non-Uniform Step Size Quantization for Accurate Post-Training Quantization, ECCV, 2022
Non-uniform quantization
[Review] MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases, ICML, 2024
Sub-billion scale LLM
[Review] Improved Feature Distillation via Projector Ensemble, NeurIPS, 2022
FC Layer Ensemble을 이용한 Feature based KD
[Review] Anomaly Detection via Reverse Distillation from One-Class Embedding, CVPR, 2022
Knowledge Distillation을 이용한 Anomaly detection
[Review] Rethinking Soft Labels For Knowledge Distillation: A Bias-Variance Tradeoff Perspective, ICLR, 2021
Variance와 Bias 관점에서의 Knowledge Distillation
[Review] Distilling the Knowledge in a Neural Network, NIPS, 2014
Knowledge Distillation 분야의 시작
Deep Learning
[PRML] 패턴인식과 머신 러닝 Ch1. 소개 - intro(1)
요하네스 케플러는 티코 브라헤가 축적해 놓은 대량의 천문학 데이터에서패턴을 찾아내어 케플러의 행성 운동 법칙을 발견했다
NLP
맨 위로 이동 ↑밑시딥
맨 위로 이동 ↑Machine Learning
[PRML] 패턴인식과 머신 러닝 Ch1. 소개 - intro(1)
요하네스 케플러는 티코 브라헤가 축적해 놓은 대량의 천문학 데이터에서패턴을 찾아내어 케플러의 행성 운동 법칙을 발견했다
Model Compression
[Review] Rethinking Soft Labels For Knowledge Distillation: A Bias-Variance Tradeoff Perspective, ICLR, 2021
Variance와 Bias 관점에서의 Knowledge Distillation
[Review] Distilling the Knowledge in a Neural Network, NIPS, 2014
Knowledge Distillation 분야의 시작
Weight Averaging
[Review] SQWA: Stochastic QuantizedWeight Averaging for Improving the Generalization Capability of Low-Precision Deep Neural Networks, ICASSP, 2021
Stocahstic Weight Averaging
[Review] Averaging Weights Leads to Wider Optima and Better Generalization, IJAI, 2018
Stocahstic Weight Averaging
Blog
Markdown PDF 변환 시 Latex Math 수식 깨짐 현상 해결 방법
Markdown PDF 변환 시 Latex Math 수식 깨짐 현상 해결 방법
VAE
맨 위로 이동 ↑AutoEncoder
맨 위로 이동 ↑Optimizer
Optimizer 정리
알고 쓰자 Optimizer
Pandas
Pandas 기본 정리
자꾸 까먹어서 기본 정리해두기
Anomaly Detection
[Review] Anomaly Detection via Reverse Distillation from One-Class Embedding, CVPR, 2022
Knowledge Distillation을 이용한 Anomaly detection