Sitemap

cs
- ai
  - control
    - (CYHB13) Definability of Truth in Probabilistic Logic (2016-08-19)
    - (SF15) Questions of reasoning under logical uncertainty (2016-08-19)
    - AAML workshop (2017-04-01)
    - AI Control References (2016-02-27)
    - Alignment for advanced machine learning systems (2017-02-01)
    - Concrete problems in AI safety (2017-02-01)
    - Conversation with Paul Christiano (2017-02-28)
    - Game theory and decision theory (2017-02-12)
    - Lob's Theorem (2016-08-19)
    - Logical induction (2017-02-01)
    - Newcomb's Problem (2016-04-22)
    - Technical agenda (2016-08-19)
    - UDT (2017-02-19)
  - Theorem proving with modern ML (2017-09-05)
- functional_programming
  - Arrows (2016-12-31)
  - Catamorphism (2016-12-26)
  - Free monads (2016-12-27)
  - Haskell (2016-04-03)
  - Haskell extensions (2016-12-25)
  - Higher-order abstract syntax (2016-12-26)
  - Neural nets in Haskell (2016-12-25)
- neural_nets
  - Neural net experiments (2016-08-03)
  - Tensorflow setup (2016-07-22)
- PL
  - LLVM tutorial (2016-07-31)
- type_theory
  - Type theory (2016-07-31)
  - Types and programming languages, Benjamin Pierce (2016-07-31)
- Semantic shared response (2016-09-24)
math
- algebra
  - linear
    - matrix_analysis
      - Matrix perturbation (2016-08-30)
    - Perron-Frobenius Theorem (2016-03-03)
- analysis
  - metric
    - Geometric functional analysis (2016-04-20)
    - MAT529 notes (2016-02-29)
    - Type and Cotype (2016-03-14)
  - numerical
    - Approximation theory and approximation practice (2016-08-08)
    - Chebyshev polynomials (2016-08-04)
- calculus
  - Calculus formulas (2016-02-27)
- logic
  - Finite model theory (2016-10-14)
  - Logic of provability (2016-08-25)
  - Questions (2017-02-19)
- probability
  - random_matrices
    - High-dimensional probability (2016-08-01)
    - Matrix concentration (2016-03-13)
  - Brownian Motion (2017-03-07)
  - Martingales (2016-04-08)
  - Stochastic calculus (2017-03-08)
- statistics
  - Fisher information (2016-04-04)
  - Maximum entropy distributions (2016-04-04)
summaries
- Conversation with Zeev 2-24-16 (2016-02-27)
- Notes index (2016-04-08)
- Weekly summary 2016-08-06 (2016-08-06)
- Weekly summary 2016-08-13 (2016-08-13)
- Weekly summary 2016-08-27 (2016-08-27)
- Weekly summary 2016-09-03 (2016-08-30)
- Weekly summary 2016-09-10 (2016-09-04)
- Weekly summary 2016-09-17 (2016-09-19)
- Weekly summary 2016-09-24 (2016-09-23)
- Weekly summary 2016-10-01 (2016-09-26)
- Weekly summary 2016-10-08 (2016-10-08)
- Weekly summary 2016-10-15 (2016-10-10)
- Weekly summary 2016-10-22 (2016-10-19)
- Weekly summary 2016-10-29 (2016-10-24)
- Weekly summary 2016-11-05 (2016-10-31)
- Weekly summary 2016-11-12 (2016-11-07)
- Weekly summary 2016-11-19 (2016-11-14)
- Weekly summary 2016-12-03 (2016-11-28)
- Weekly summary 2016-12-10 (2016-12-10)
- Weekly summary 2016-12-17 (2016-12-17)
- Weekly summary 2017-02-25 (2017-02-21)
- Weekly summary 2017-03-11 (2017-03-07)
- Weekly summary 2017-03-18 (2017-03-18)
- Weekly summary 2017-04-08 (2017-04-03)
- Weekly summary 2017-04-29 (2017-04-25)
- Weekly summary 2017-07-22 (2017-07-18)
- Weekly summary 2017-09-09 (2017-09-05)
- Weekly summary 2018-11-10 (2018-11-07)
- Weekly summary 4-2-16 (2016-04-02)
- Weekly summary 4-30-16 (2016-04-30)
- Weekly summary 4-9-16 (2016-04-04)
- Weekly summary 5-14-16 (2016-05-11)
tcs
- algorithmic_game_theory
  - Nash equilibrium (2016-08-31)
- algorithms
  - Algorithms (2016-03-03)
  - Goemans-Williamson (2016-04-02)
- coding
  - (Bar13) Convexity of the image of a quadratic map via the relative entropy distance (2016-04-02)
  - LCC lower bounds by geometry (2016-04-02)
  - LDC's - directions (2016-05-01)
  - LDCs (2016-03-03)
  - Perfect LCCs (2016-04-13)
  - Thoughts on LDC's (2016-03-14)
  - Thoughts on LDC's (2016-03-21)
- complexity
  - (Rem16) The Hilbert Function, Algebraic Extractors, and Recursive Fourier Sampling (2016-02-29)
  - Learning to model structures and data (2017-03-12)
  - Recursive Fourier Sampling (2016-02-29)
  - Scraps (2016-02-29)
  - Sum of squares (2016-03-24)
- information_theory
  - Real channels (2016-02-27)
- machine_learning
  - community
    - (GRSY15) How Hard is Inference for Structured Prediction? (2016-03-03)
    - (MNS12) (2016-02-28)
    - (SD15) Minimax rates for memory-bounded sparse linear regression (2016-02-29)
    - Censored block model (2016-02-28)
  - matrices
    - (A16) Provable algorithms for inference in topic models (2016-04-04)
    - (AGM14) New algorithms for learning incoherent and overcomplete dictionaries (2016-04-02)
    - (AGMM15) Simple, efficient, and neural algorithms for sparse coding (2016-03-25)
    - (BGKP16) Non-negative matrix factorization under heavy noise (2016-06-27)
    - (BH16) Algorithms for generalized topic modeling (2016-08-12)
    - CCA (Canonical correlation analysis) (2016-06-28)
    - DL experiments (2016-10-17)
    - DL generalization (2016-09-19)
    - Factor analysis (2016-06-28)
    - ICA (Independent components analysis) (2016-06-28)
    - Inference for topic models - Code (2016-05-18)
    - k-means clustering (2016-06-28)
    - LDA (Linear discriminant analysis) (2016-09-04)
    - Linear dimensionality reduction ([CG15]) (2016-06-28)
    - Matrix factorizations (2016-04-04)
    - NMF algorithm (2016-04-22)
    - Non-negative matrix factorization (2016-03-26)
    - Relevant coordinates (2016-06-02)
    - Relevant coordinates - Low-rank (2016-06-07)
    - Towards a better understanding of streaming PCA (Yuanzhi Li) (2016-05-10)
  - neural_nets
    - (ALM16) WHY ARE DEEP NETS REVERSIBLE - A SIMPLE THEORY, WITH IMPLICATIONS FOR TRAINING (2016-03-13)
    - (CHMAL15) The Loss Surfaces of Multilayer Networks (2016-03-07)
    - (CW17) Adversarial Examples Are Not Easily Detected - Bypassing Ten Detection Methods (2018-04-05)
    - (JSA15) Beating the Perils of Non-Convexity - Guaranteed Training of Neural Networks using Tensor Methods (2016-06-27)
    - (PMDH16) Convolutional Patch Representations for Image Retrieval - an Unsupervised Approach (2016-09-26)
    - (TPGB17) The space of transferable adversarial examples (2017-05-24)
    - AdaGAN (2017-02-24)
    - Adversarial examples in neural networks (2017-02-21)
    - Adversarial experiments (2017-03-02)
    - Adversarial thoughts (2017-04-16)
    - Analysis of neural networks (2016-03-05)
    - Complexity of neural networks (2016-07-25)
    - Confidence in neural nets (2017-04-03)
    - Convnets ideas (2016-08-02)
    - GANs (2016-12-28)
    - Interpretable neural nets (2016-10-12)
    - Learning structured, robust, and multimodal deep models (2016-10-21)
    - LSTM Programming (2016-03-19)
    - Musings on Barron's Theorem (2016-12-22)
    - Neural net learning, Anthony and Bartlett (2017-02-28)
    - Neural net separation (2017-02-09)
    - Neural nets as kernel space (2017-03-23)
    - Neural nets basics (2016-03-13)
    - Neural nets learn dictionaries (2016-10-10)
    - PCANet - A simple deep learning baseline for image classification? (2016-09-10)
    - PMI for images (2016-08-01)
    - PMI for images (scratch) (2016-08-01)
    - Tensorflow setup (2017-03-03)
  - nlp
    - (AKV17) A sparse recovery view of sentence embeddings, bag of n-grams, and LSTMs (2017-07-18)
    - (ALLMR16) Linear Algebraic Structure of Word Senses, with Applications to Polysemy (2016-03-15)
    - (ALLMR16) RAND-WALK - A latent variable model approach to word embeddings (2016-03-15)
    - (HA16) Unsupervised Learning of Word-Sequence Representations from Scratch via Convolutional Tensor Decomposition (2016-08-02)
    - (MVB16) Geometry of Polysemy (2016-10-28)
    - Alexa (2016-10-13)
    - Combinatory Categorial Grammar (2018-01-01): How we all speak in functions
    - Embedding methods in NLP (2016-12-06)
    - Language games (2016-10-13)
    - Learning grammar (2017-10-04)
    - NLP (2016-05-04)
    - NLP 2016 Senior presentations (2016-05-14)
    - Percy Liang's papers (2016-05-04)
    - PMI and feature vectors (2016-07-29)
  - optimization
    - (AO15) Linear coupling (2016-03-06)
    - (HKY17) Hyperparameter Optimization - A Spectral Approach (2017-07-19)
    - (HMR16) Gradient descent learns linear dynamical systems (2016-12-27)
    - (SV16) The mixing time of the Dikin walk in a polytope - a simple proof (2016-09-07)
    - Accelerated Gradient descent (2016-03-05)
    - Bandit convex optimization (2016-10-11)
    - Constrained optimization (2016-04-28)
    - Convex optimization (2016-03-04)
    - Convex problems (2016-04-23)
    - Convexity (2016-04-23)
    - Distribution of critical points (2016-08-13)
    - Duality (2016-03-04)
    - Ellipsoid method (2016-08-30)
    - Generalization of neural nets (2016-10-10)
    - Gradient descent (2016-03-04)
    - Hierarchies of convex relaxations (2016-12-28)
    - Interior point methods (2016-08-26)
    - Legendre transform (2016-12-28)
    - Mirror descent (2016-03-05)
    - Sampling (2016-05-17)
    - SDP duality (2016-03-04)
    - Second-order methods (2016-04-22)
    - SGD Variance Reduction (2016-03-04)
    - The Blessing and the Curse of the Multiplicative Updates (2017-02-12)
  - probabilistic
    - (DKLPRS) Markov logic (2016-05-17)
    - (R16) How to calculate partition functions using convex programming hierarchies - provable bounds for variational methods (2016-12-28)
    - (WJ08) Graphical Models, Exponential Families, and Variational Inference (2016-09-30)
    - Annealed importance sampling (2017-07-20)
    - Hidden Markov Models (2016-10-11)
    - Langevin dynamics (2017-03-15)
    - Probabilistic models - Ideas (2016-11-07)
    - Variational Bayes (2017-02-06)
  - reinforcement_learning
    - Control theory (2017-12-24)
    - Control theory (2016-12-06)
    - Function approximation (2016-11-01)
    - Inverse RL (2017-04-03)
    - Linear convex regulator (2016-12-14)
    - Linear convex regulator 2 (2017-01-10)
    - Linear quadratic regulator (2016-12-09)
    - MDP's with continuous state space (2016-10-14)
    - MDP's with continuous state space (scratch) (2016-10-14)
    - Policy gradient (2016-11-22)
    - POMDPs (2016-11-29)
    - Reinforcement learning (2016-09-28)
    - Reinforcement learning convergence (2016-10-24)
    - Reinforcement learning theory (2016-10-22)
    - RL references (2016-10-25)
  - representation
    - (AR17) Provable benefits of representation learning (2017-07-18)
  - tensors
    - (BKS15) Dictionary Learning and Tensor Decomposition via the Sum-of-Squares Method (2016-08-30)
    - Tensor decomposition (2016-08-30)
  - (HM16) A non-generative framework and convex relaxations for unsupervised learning (2016-12-27)
  - Boosting (2017-02-08)
  - CART and random forests (2016-06-29)
  - Interests (2016-03-13)
  - Kernels (2016-12-29)
  - Multiplicative weights (2017-02-24)
  - Representation learning (2016-07-28)
  - Self-taught learning ([RBLPN07] Self-taught Learning - Transfer Learning from Unlabeled Data) (2016-08-31)
  - Stanford quals (2016-06-29)
  - Transductive learning (2016-08-31)
  - Transfer learning (2016-12-29)
- networks
  - Spectral Bounds for Stochastic Diffusion Model in Networks (2016-03-08)
test
- Test (2016-02-27)