Areas of interest: machine learning, graphical models, signal processing, information theory, compressed sensing, convex optimization; dynamical systems, functional data analysis / spatial statistics / shape analysis
Models of interest: Independent Component/Subspace Analysis, Mixture of Kalman Filters; network models; topic models; differential equation models; Non-Parametric Bayes; structured data.
Neat ideas: geometry of exponential families, n-ary relational learning, automatic optimization, manifold learning, information bottleneck method, low-rank matrix completion, unfolding flower models, probabilistic programming languages
tutorials- Introduction to Kolmogorov Complexity (with Liliana Salvador) (slides), 45 minutes.
- Introduction to Machine Learning and Bayesian inference (slides), 45 minutes.
video demosslice sampling
general-purpose codeR: R-helpers
papers all publications Google ScholarG. Lacerda - Identification of gene modules using a generative model for relational data - UBC Master's thesis (2010), supervised by Jennifer Bryan.
G. Lacerda, P. Spirtes, J. Ramsey, P.O. Hoyer - Discovering Cyclic Causal Models by ICA (UAI2008), video lecture with slides) extends LiNGAM to discover cyclic models; The non-Gaussian model leads to a finer level of identifiability than what can be achieved in the Gaussian case (e.g. by Richardson's CCD), and allows us to relax the faithfulness assumption.
P. O. Hoyer, A. Hyvärinen, R. Scheines, P. Spirtes, J. Ramsey, G. Lacerda, and S. Shimizu - Causal discovery of linear acyclic models with arbitrary distributions Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence (UAI-2008)
How to intelligently combine LiNGAM with methods based on conditional independence tests. This is useful when it may be the case that more than one, but not all error terms are Gaussian.
G. Lacerda - Upper-Bounding Proof Length with the Busy Beaver (2008) - I derive an (uncomputable) upper bound on the length of the shortest proof of any given statement, as a function of the length of the statement; and briefly discuss implications. Mathematically trivial, but apparently original.
N. Matsuda, W. Cohen, J. Sewall, G. Lacerda, and K. R. Koedinger (2008) - Why tutored problem solving may be better than example study: Theoretical implications from a simulated-student study. In Proceedings of the International Conference on Intelligent Tutoring Systems.
N. Matsuda, W. Cohen, J. Sewall, G. Lacerda, and K. R. Koedinger (2007) - Predicting students performance with SimStudent that learns cognitive skills from observation. In R. Luckin, K. R. Koedinger & J. Greer (Eds.), Proceedings of the international conference on Artificial Intelligence in Education (pp. 467-476). Amsterdam, Netherlands: IOS Press.
N. Matsuda, W. Cohen, J. Sewall, G. Lacerda, and K. R. Koedinger - Evaluating a Simulated Student using Real Students Data for Training and Testing, In C. Conati, K. McCoy & G. Paliouras (Eds.), Proceedings of the international conference on User Modeling (LNAI 4511) (pp. 107-116). Berlin, Heidelberg: Springer.
S. F. Adafre, W. R. van Hage, J. Kamps, G. Lacerda, and M. de Rijke - The University of Amsterdam at CLEF 2004, In: C. Peters and F. Borri, editors, Working Notes for the CLEF 2004 Workshop, pages 91-98, 2004.
getting helpQ&A sites for Math: mathoverflow, math.stackexchange
Q&A sites for Machine Learning / Stats: CrossValidated, MetaOptimize
For R, visit the #R channel on FreeNode (IRC). Emacs users can use IRC by doing "M-x erc".
If your problem is computationally intensive, consider learning distributed programming (GPU or cluster).
work toolsErgonomics: standing desk, high chair, white boards
Programming languages: Julia, R, Matlab, Python, bash
Programming tools: emacs, automatic memoization
Writing: knitr, pandoc, LyX, ShareLatex
Online notebook: MediaWiki
Data collection: BeautifulSoup, curl
Reference management: Zotero
misc toolsBeeminder, Boomerang, Dropbox, HelloSign, Google Calendar (social features, add events with one click), TotalFinder, SSHFS
"a unique translation tool combining an editorial dictionary and a search engine"
Google Translate tooltip
learn a new language / help translate documents; very clever crowdsourcing.
some things I likeargument mapping, bikes, bluegrass, contact improvisation, DreamWidth, functional programming, GiveWell, infoviz, musical instruments, open data, Quantified Self
food for thought"You and Your Research", by Richard Hamming
"Why People Are Irrational about Politics", by Michael Huemer
"Why I defend scoundrels", by Yvain
Paul Graham: "How to do Philosophy", "Why nerds are unpopular"
LessWrong: Applause Lights
"Illusion of Transparency: Why No One Understands You"
Ribbonfarm: "A Big Little Idea Called Legibility"
Ben Goldacre: "The Information Architecture of Medicine is Broken"
blogsAndrew Gelman - Statistical Modeling, Causal Inference, and Social Science
Cosma Shalizi - Three-Toed Sloth
Cathy O' Neil - mathbabe
Peter Gray - Freedom to Learn
neat toysAlgodoo: 2D physics engine
BeepBox: chiptune editor