Kevin's Notes
Search
CTRL + K
Kevin's Notes
Search
CTRL + K
School Notes
CS341
BFS
CS 341 Algorithms
Decision Problems
Divide and Conquer
Dynamic Programming
Graph Algorithms
Greedy
NP-Completeness
NP-Hardness
Reductions
CS348
Additional Dependencies and Normal Forms
Aggregation
Always Good Transformations
Armstrong’s Axioms
Attributes
Basic ER Diagrams
Beyond Standard Physical Design
Boyce-Codd Normal Form
Change Anomalies
Co-Clustering Indices
Concurrency Control
Cost Estimation
Cost of Relational Operations
Cost of Retrieval
CS 348 Intro to Database Management Systems
Data Dependencies
Database Tuning
Deadlocks
Dependency Preserving
Diagnosis and Repair
Entity Sets
Expressiveness
Extended Features
Failure Recovery
Formal Properties of Good Design
Functional Dependencies
Generalization
Good Decomposition
Implementation
Inserts and Deletes
Isolation Levels
Join Order Selection
Keys
Logging
Logical Consequence
Logical Mapping
Logical Schema and Query Tuning
Lossless-Join
Minimal Cover
Normal Form
Physical Database Design
Query Evaluation
Query Optimization
Query
Relation Names
Relational Algebra
Relational Schema Good Design
Relationship Sets
Schedules
Semantics
Size Estimation
Specialization
Third Normal Form
Transaction and Recovery Management
Transactions
Triple Store
Two-Phase Locking
Two-Tier Architecture
Views
Weak Entity Sets
Workload Modelling
CS350
Case Studies
Golang
Speeding up FS
XFS
Reading Assignments
Fast File System
Lottery Scheduling
80⧸20 Rule
Address Space
Allocation Groups
Amdahl’s Law
Application Binary Interface
B+ Trees
Base + Bound Register
Belady’s Anomaly
Block Allocation
Borrowed Virtual Time Scheduler
Bus
C11 Atomics
Cache Coherence
Coarse-grained locking
Concurrency
Condition Variables
Context Switch
Contiguous Allocation
Cost model for disk I⧸O
CPU Bound
Crash Recovery
Critical Section
Cross-allocation
CS 350 Operating Systems
Cylinder
Deadlock
Device Drivers
Direct Memory Access
Directories
Disk Interface
Disk Performance
Disk positioning system
Disk
Eviction Policies
Exceptions
Execution Context
Extent Based
FAT
FCFS Scheduling
File Systems
Files
Fine-grained locking
Flash memory
Fragment Allocation
Fragmentation
Function in x86
Hard Links
Hardware Interrupt Handling Process
Hardware Specific Synchronization Instructions
Hierarchical UNIX
Implementation of Process
Implementation of Thread
Indexed Files
Inode
Interrupt Descriptor Table
Interrupt Gate Descriptor
Interrupts
Introduction to Operating Systems
I⧸O and Devices
I⧸O Bound
Journaling
Kernel mode
Kernel Thread
Kernel view
Linked Files
Load-time Linking
Lockset Algorithm
Magnetic Platters
MCS Lock
Memory Management Unit
Memory mapped files
Memory
Monitors
Multi-level Indexed Files
Multicore Caches
Multilevel feedback queues
Multitasking
Mutex
NAND flash
OS Kernel
Paging
Performance of File Systems
Pmap Layer
POSIX Files API
POSIX Interface
POSIX Processes API
POSIX Threads API
Priority Donation
Priority Scheduling
Process Priority
Process states
Processes
Protection
PThead Mutex API
PThread CV API
Registers
Round Robin Scheduling
Scheduling Criteria
Scheduling
SCSI
Secondary storage
Sectors
Seek
Segmentation
Semaphores
Sequential Consistency
SJF Scheduling
Soft Links
Soft Updates
Speed
Spinlock
Superblock
Superpages
Switchframe
Synchronization
System Call Interface
System Calls
Thrashing
Thread Dependencies
Threads
Time Quantum
TLB
Tracks
Trapframe
Types of flash memory
Types of Operating Systems
Typical OS Structure
User Thread
User view
Virtual Memory
Wait Channel
Working Set Model
x86 Atomicity
x86 Consistency
CS484 (HKU)
3D Shape Representations
3D Vision
Activation Function
AdaGrad
Adam
Attention
Autoencoders
Backpropagation and Neural Networks
Backpropagation
Batch Normalization
Choosing Hyperparameters
CNN Architectures
Computational Graph
Convolution Layers
Convolutional Neural Networks
CS 484 Computer Vision
Data Augmentation
Data Preprocessing
Diffusion
Dropout
Early Stopping
Elastic net
Feature Extraction
Fully visible belief network (FVBN)
Generative Adversarial Networks
Generative Models
Gradient Descent
Gradient
Hyperparameters
Image Classification
Image Classifier
Instance Normalization
Instance Segmentation
L1 Distance
L1 Regularization
L2 Distance
L2 Regularization
Layer Normalization
Learning Rate
Linear Classification
Loss Function
Loss Functions & Optimizations
Model Ensembles
Multiclass SVM Loss
Nearest Neighbour
Neural Networks
Normalization
Object Detection
Optimization
Pooling Layers
Recurrent Neural Networks
Regularization
Self-Attention Layer
Self-Supervised Learning
Semantic Segmentation
Softmax Classifier
Stochastic Gradient Descent
Training Neural Networks
Transfer Learning
Transformers
Videos
Vision and Language
Weight Initialization
Home
L1 Distance
AKA Manhattan Distance
Compare individual pixels of the image
d
1
(
I
1
,
I
2
)
=
∑
p
|
I
1
p
−
I
2
p
|
