Robot Updated at:22 Jan 2025 21:09:21 GMT

Author: yiliuyan161

docs/awesome/awesome-agi-cocosci.md

@@ -240,7 +240,7 @@ Contributions are greatly welcomed! Please refer to [Contribution Guidelines](ht
 
 * [Latent Space Factorisation and Manipulation via Matrix Subspace Projection](http://proceedings.mlr.press/v119/li20i.html) - ***ICML'20***, 2020. [[All Versions](https://scholar.google.com/scholar?cluster=9592355331559392684&hl=en&as_sdt=0,5)].
 
-* [Minimax entropy principle and its application to texture modeling](https://www.dam.brown.edu/people/mumford/vision/papers/1997e--MinimaxEntropy-NC.pdf) - ***Neural Computing***, 1997. [[All Versions](https://scholar.google.com/scholar?oi=bibs&hl=en&cluster=407872717119429940)].
+* [Minimax entropy principle and its application to texture modeling](https://ieeexplore.ieee.org/abstract/document/6796444) - ***Neural Computing***, 1997. [[All Versions](https://scholar.google.com/scholar?cluster=407872717119429940)]. [[Preprint](https://www.dam.brown.edu/people/mumford/vision/papers/1997e--MinimaxEntropy-NC.pdf)]. This article proposes a general theory and methodology, called the minimax entropy principle, for building statistical models for images (or signals) in a variety of applications. This principle consists of two parts. The first is the maximum entropy principle for feature binding (or fusion): for a given set of observed feature statistics, a distribution can be built to bind these feature statistics together by maximizing the entropy over all distributions that reproduce them. The second part is the minimum entropy principle for feature selection: among all plausible sets of feature statistics, we choose the set whose maximum entropy distribution has the minimum entropy. Computational and inferential issues in both parts are addressed; in particular, a feature pursuit procedure is proposed for approximately selecting the optimal set of features. The minimax entropy principle is then corrected by considering the sample variation in the observed feature statistics, and an information criterion for feature pursuit is derived. The minimax entropy principle is applied to texture modeling, where a novel Markov random field (MRF) model, called FRAME (filter, random field, and minimax entropy), is derived, and encouraging results are obtained in experiments on a variety of texture images.
 
 * [Parameter Expansion for Data Augmentation](https://www.tandfonline.com/doi/abs/10.1080/01621459.1999.10473879) - ***Journal of the American Statistical Association***, 1999. [[All Versions](https://scholar.google.com/scholar?cluster=15342818142955984734)]. [[Preprint](http://www.stat.ucla.edu/~ywu/research/papers/PXDA.pdf)]. Viewing the observed data of a statistical model as incomplete and augmenting its missing parts are useful for clarifying concepts and central to the invention of two well-known statistical algorithms: expectation-maximization (EM) and data augmentation. Recently, the authors demonstrated that expanding the parameter space along with augmenting the missing data is useful for accelerating iterative computation in an EM algorithm. The main purpose of this article is to rigorously define a parameter expanded data augmentation (PX-DA) algorithm and to study its theoretical properties. The PX-DA is a special way of using auxiliary variables to accelerate Gibbs sampling algorithms and is closely related to reparameterization techniques.
 

docs/awesome/awesome-angular.md

@@ -1246,6 +1246,7 @@ to simplify usage and allow quick customization.
 * [@marxlnfcs/ngx-grid](https://github.com/marxlnfcs/ngx-grid) - Angular library to create a simple grid layout.
 * [ngx-flexbox](https://github.com/philipibovo/ngx-flexbox) - Designed as an alternative to [@angular/flexlayout](https://github.com/angular/flex-layout), ngx-flexbox provides Angular developers with component layout features using a custom layout API, media query observables, and injected DOM flexbox-2016 CSS stylings.
 * [ngx-van](https://github.com/otodockal/ngx-van) - Tiny replacement for HTML nav element with mobile side nav menu built-in. Good old nav element on desktop, sliding side nav on mobile. No duplication.
+* [ngx-swipe-menu](https://github.com/charlesschaefer/ngx-swipe-menu) - A component to create "swipe left to 'action'" experiences.
 
 #### Loaders
 

docs/awesome/awesome-audit-algorithms.md

@@ -11,6 +11,10 @@ Nowadays, many algorithms (recommendation, scoring, classification) are operated
 
 ## Papers
 
+### 2025
+- [CALM: Curiosity-Driven Auditing for Large Language Models](https://arxiv.org/abs/2501.02997) - (AAAI) *Auditing as a black-box optimization problem where the goal is to automatically uncover input-output pairs of the target LLMs that exhibit illegal, immoral, or unsafe behaviors.*
+- [Queries, Representation & Detection: The Next 100 Model Fingerprinting Schemes](https://arxiv.org/abs/2412.13021) - (AAAI) *Divides model fingerprinting into three core components, to identify ∼100 previously unexplored combinations of these and gain insights into their performance.*
+
 ### 2024
 - [Auditing Local Explanations is Hard](https://arxiv.org/abs/2407.13281) - (NeurIPS) *Gives the (prohibitive) query complexity of auditing explanations.*
 - [LLMs hallucinate graphs too: a structural perspective](https://arxiv.org/abs/2409.00159) - (complex networks) *Queries LLMs for known graphs and studies topological hallucinations. Proposes a structural hallucination rank.*
@@ -119,6 +123,9 @@ ranking and review recommendation systems, with demographic parity, exposure, an
 
 ## Related Events
 
+### 2025
+* [AAAI workshop on AI Governance: Alignment, Morality, and Law](https://aaai.org/conference/aaai/aaai-25/workshop-list/#ws06)
+
 ### 2024
 * [1st International Conference on Auditing and Artificial Intelligence](https://www.ircg.msm.uni-due.de/ai/)
 * [Regulatable ML Workshop (RegML'24)](https://regulatableml.github.io/)

docs/awesome/awesome-board-games.md

@@ -1679,7 +1679,7 @@
 | ------: | -------: | -----: |
 |  3 - 10 |        8 | 10-15m |
 
-### [Who Wants to Be a Millionare](http://www.boardgamecapital.com/who-wants-to-be-a-millionaire-rules.htm)
+### [Who Wants to Be a Millionare](https://www.boardgamecapital.com/who-wants-to-be-a-millionaire-rules.htm)
 
 > Ever wanted to play the popular Game Show game Who Wants To Be A Millionaire? Check out this board game version of Who Wants To Be A Millionaire. Other than the TV cameras, Regis Philbin, and the real money, this is the same game including easy laughable \$100 questions, life lines, and a over 2,000 questions.
 

docs/awesome/awesome-elixir.md

@@ -113,6 +113,7 @@ There are [other sites with curated lists of elixir packages](#other-awesome-lis
 * [exchat](https://github.com/tony612/exchat) - A Slack-like app by Elixir, Phoenix & React (redux).
 * [Exon](https://github.com/tchoutri/Exon) - A “mess manager” developed in Elixir and provides a simple API to manage & document your stuff. ([Docs](https://hexdocs.pm/exon/readme.html)).
 * [ExShop](https://github.com/authentic-pixels/ex-shop) - Digital goods shop & blog created using Phoenix framework.
+* [Harpoon](https://github.com/aschiavon91/harpoon) - A webhook receiver/inspector app, made using Phoenix and LiveView, it's basically a simplified version of [webhook.site](htts://webhook.site).
 * [Hydra](https://github.com/doomspork/hydra) - A multi-headed beast: API gateway, request cache, and data transformations.
 * [Igthorn](https://github.com/cinderella-man/igthorn) - Cryptocurrecy trading platform / trading bot with admin panel.
 * [Lynx](https://github.com/clivern/lynx) - A Fast, Secure and Reliable Terraform Backend, Set up in Minutes.