Index

Recently, I've started using org-roam to take notes in the Zettelkasten style. I've found these notes to be helpful both in reviewing old material and keeping track of new information.

In my reading, whenever I come across a concept that I haven't seen or don't remember well, I make a new note. These notes aren't organized into categories or hierarchies, but connections between notes exist as links and back-links.

• functors (haskell)
• applicative functors (haskell)
• Types in Haskell
• Device File
• Partition
• File Systems
• inode
• Mount
• Virtual File System
• System Call
• Installing a new drive
• Unified Extensible Firmware Interface
• Boot Process
• Dynamic Host Configuration Protocol
• Network Managers on Arch
• Arch post-install
• Linux Backup
• Devlin et al 2018 - BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
• Vaswani et al 2017 - Attention Is All You Need
• Attention
• Transformer
• Lu et al 2019 - ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
• Carion et al 2020 - End-to-End Object Detection with Transformers
• Residual blocks
• layer normalization
• Kinds in Haskell
• Typeclasses in Haskell
• Currying in Haskell
• Feature Pyramid Networks for Object Detection
• Convolutional Networks
• Ren et al 2015 - Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
• Region of Interest Pooling
• Assignment Problem
• Erler 2010 - Does Memory Modification Threaten Our Authenticity?
• Memory
• Rejection Sampling
• Inverse transform sampling
• probability integral transform
• Blogs
• Pointers in C
• Machine Code
• Registers
• Assembly Language
• Compilers
• Compiler Example: C to Assembly
• Modern Compilers
• How compilers handle procedure calls
• Baye's Rule
• Entropy
• Decision Trees
• Kullback-Leibler divergence
• Gini impurity
• Convergence Almost Surely
• Convergence in Probability
• Publish org notes to HTML
• Information Content
• Jensen's Inequality
• Law of the unconscious statistician
• lazy evaluation
• Combinators
• Y Combinator
• Maximum Likelihood Estimation
• Joint Entropy
• Kraft-McMillan Inequality
• softmax
• Cross Entropy
• sigmoid
• Hierarchical Softmax
• Mikolav et al 2013 - Distributed Representations of Words and Phrases and their Compositionality
• CYK Algorithm
• Law of Large Numbers
• Bayesian Inference
• Frequentist vs Bayesian Inference
• Policy Gradient
• Markov's Inequality
• Semantic Parsing
• Dunietz et al 2020 - To Test Machine Comprehension, Start by Defining Comprehension
• Peters et al 2018 - Deep contextualized word representations
• Tenney et al 2019 - BERT Rediscovers the Classical NLP Pipeline
• Ramsey Number
• Pascal's Rule
• Synecdoche vs Metonymy
• Cross Validation
• Firth 1957 - A Synopsis of Linguistic Theory
• TF-IDF
• Turney and Pantel 2010 - From frequency to meaning: Vector space models of semantics
• Precision vs Recall
• Reduction
• Model Theory
• Semantic Theory of Truth (Tarski)
• Frege's theory of sense and denotation
• Intuitionistic Type Theory
• Sampling
• greatest common denominator
• (markov chains) aperiodicity
• Metropolis-Hastings
• Markov Chain Monte Carlo
• Monads
• Importance Sampling
• Linker
• LSTM
• Scalar Implicature
• Grice's Maxims
• Goodman and Frank 2016 - Pragmatic Language Interpretationas Probabilistic Inference
• Referential Transparency
• Git rebase vs merge
• Git reset vs checkout
• Expectation Maximization
• Zero configuration networking
• Arch printing
• ssh
• grad school advice
• git submodule
• reinforcement learning
• multi-armed bandit problem
• Actor Critic
• Papadimitriou et al 2020 - Brain computation by assemblies of neurons
• Conferences and Journals
• research reading list
• Hu and Singh 2021 - Transformer is All You Need: Multimodal Multitask Learning with a Unified Transformer
• Merrill 2021 – Formal Language Theory Meets Modern NLP
• hammersley-clifford theorem
• https
• Prasanna 2020 – When BERT Plays The Lottery, All Tickets Are Winning
• Marasović 2018 – NLP’s generalization problem, and how researchers are tackling it
• Conneau and Lample 2018 – Word Translation without Parallel Data
• Ruder 2019 – The 4 Biggest Open Problems in NLP
• mutual information
• source coding theorem
• noisy channel coding theorem
• gumbel distribution
• gumbel max trick
• reparameterization trick
• gumbel softmax
• spearman's rank correlation coefficient
• pearson correlation coefficient
• conditional entropy
• Convergence in Distribution
• central limit theorem
• satisfiability modulo theories
• Chernoff bound
• change of basis
• conditional dependence
• rent seeking
• lagrange multipliers
• Qin and Eisner 2021 – Learning How to Ask: Querying LMs with Mixtures of Soft Prompts
• policy iteration
• Antoniak and Mimno 2021 – Bad Seeds: Evaluating Lexical Methods for Bias Measurement
• value iteration
• off-policy policy gradient
• Trust Region Policy Optimization
• Proximal Policy Optimization
• Dai and Yang 2019 – Transformer-XL: Attentive language models beyond a fixed-length context
• Gaussian Processes
• perplexity
• multiple dispatch
• Dehghani et al 2021 – The Benchmark Lottery
• sufficient statistic
• Bellman equation
• Mnih et al 2013 – Playing Atari with Deep Reinforcement Learning (Deep Q-Learning)
• probability space
• Measures and Probability Measures
• Sigma Field
• Caratheodory's Extension Theorem
• Lebesgue Measure
• e^x ≥ 1 + x
• independence
• conditional probability
• law of total expectation
• iterated expectation
• random variable
• cumulative distribution function
• Neyman-Pearson Lemma
• bayesian hypothesis test
• group (algebra)
• receiver operating characteristic
• hypothesis testing
• lambda calculus
• hoeffding's inequality
• polynomial interpolation
• rank nullity theorem
• phantom type
• properties of expectation
• covariance
• simpson's paradox
• bayesian network
• lebesgue integral
• Big Step Semantics
• Kim 2021 – Sequence-to-Sequence Learning with Latent Neural Grammars
• convergence in mean
• confidence interval
• one tailed hypothesis test
• parser combinator
• convergence of random variables
• bootstrapping (statistics)
• ELisp
• Bommasani et al 2021 – On the Opportunities and Risks of Foundation Models
• parametric vs non-parametric models
• assorted terms from linguistics
• statistical model
• estimator
• program semantics
• proof assistants
• probabilistic programming languages
• dirichlet distribution
• beta distribution
• generalized linear model
• graph neural network
• Dyna-Q Learning
• monte carlo tree search
• marginal likelihood
• variational bayes
• rank
• polymorphism
• parametric polymorphism
• monty hall
• monoid (haskell)
• foldable and traversable (haskell)
• degrees of freedom
• student's t test
• permuatation test
• bessel's correction
• chi squared test
• fmri
• chi squared distribution
• matrix similarity
• homoiconicity
• rust and haskell analogs
• references and borrowing in rust
• timezones
• fourier transform
• wavelets
• rust trait bounds vs trait objects
• winograd schema challenge
• predictive coding
• Belikov 2021 – Probing Classifiers: Promises, Shortcomings, and Advances
• blocking
• confounds
• build a pc
• quantum computing
• UMAP
• fisher information
• self-supervision
• bonferroni correction
• moving hardware with arch
• effect size
• spotify on linux
• short time fourier transform
• variational auto encoders
• ignorability
• Oord et al 2019 – Representation Learning with Contrastive Predictive Coding
• receptive field
• field
• vector space
• python decorators
• qubits
• quantum gates
• p-value
• Distributed Data Parallel
• EPR pairs
• quantum teleportation
• mixed effect models
• otsu thresholding
• granger causality
• causal inference
• differential privacy
• python multi-processing
• morlet wavelet
• False Discovery Rate
• optical flow
• interaction term
• generative vs discriminative
• mapping deep learning models to brain activations
• brain anatomy
• wasserstein metric
• sshfs
• tensor product
• bell's theorem
• pareto efficient
• projector
• projective measurement
• unitary matrix
• diagonalizable matrix
• projective unitary group
• center of group
• bloch sphere
• quotient group
• normal subgroup
• coset
• homomorphism
• lie group
• differentiable manifold
• topological group
• topological space
• SO(3)
• pauli matrices
• density matrices
• state space model
• CNOT
• Fredkin gate
• arch rescue
• deutsch's algorithm
• phase kickback
• graph convolutional networks
• quantum fourier transform
• hamming code
• transductive learning
• traits in rust
• read from file in rust
• landauer principle
• householder transformation
• grover's algorithm
• order finding
• phase estimation
• shor's factoring algorithm
• quantum error correcting code
• css codes
• linear algebra
• standard error
• conservation laws and symmetry
• group action
• group representation
• general linear group
• compact space
• bounded set
• closed set
• f test
• homeomorphism
• continuous function
• open set
• group representations and group actions (geometric machine learning)
• group invariant and group equivariant functions
• numpy einsum
• null space
• linear map
• rearrangement theorem (group theory)
• nominal association
• hermitian matrices
• schur's lemma
• irreducible representation
• reducible representation
• character
• regular representation
• linear discriminant analysis
• compare two time series
• generators of lie groups
• lie group representation
• spherical harmonics
• conjugancy classes
• e3nn
• label supplementary figures in latex
• compressed sensing
• poisson distribution
• exponential distribution
• spotify api
• find command
• kalman filter
• connect to wifi with tty
• brain orientations
• cozy videos
• weight decay and l2 regularization
• batch norm
• multihop port forwarding
• vqvae
• abilene paradox
• overfitting
• momentum
• anova
• nonconvex optimization
• convex optimization
• change of variables (probability distribution)
• continuity from above and below
• tensor
• covariant and contravariant
• intersection over union
• Index