A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
The paper develops a framework for fair machine learning predictions.
Detects ghostwriting in high school assignments.
This work extends the scaling law to multiple and kernel regression, challenging traditional machine learning principles.
Analyzed writing style changes in Danish high school students.
Paper uses RNNs to predict policy impacts on schooling over time.
Private learning is hard when data is long-tailed.
Study predicts high school dropout risk in Louisiana using imbalanced learning techniques.
Hierarchical causal models help understand cause and effect in nested data.
Paper proposes an ensemble classifier for balanced MBA selection data.
Deep learning detects schools of herring from echograms.
Notes on a theorem with broad applications in dynamical systems.
Hans Duistermaat was scheduled to lecture in the 2010 School on Poisson Geometry at IMPA, but passed away suddenly. This is a record of a talk I gave at the 2010 Conference on Poisson Geometry (the week after the School) to share some of my memories of him and to give a brief assessment of his impact on the subject.
Kernel ridge regression inference for nonstandard data.
These are lecture notes from the Clay Mathematics Institute summer school ``Floer Homology, Gauge Theory, and Low Dimensional Topology'' Alfred Renyi Institute; www.claymath.org/programs/summer_school/2004/. The main goal of these notes is to sketch a proof of Giroux correspondence between open book decompositions of t…
Uses Dirac geometry to prove Poisson geometry results.
Study uses echo-sounder buoys to analyze tuna schools' association with dFADs globally.
In this paper, we describe a newly discovered statistical property of time series data for daily price changes. We conducted quantitative investigation of the {\it calm-time intervals} of price changes for 800 companies listed in the Tokyo Stock Exchange, and for the Nikkei 225 index over a 27-year period from January …
Survey on curvature bounds and isoperimetric inequalities.
A simple model explains inference scaling in neural models.
This is an introductory text to differential geometry (written in Polish) aimed for high-school students.
New methods for fair interventions using causal modeling.
In this paper we propose two new algorithms based on biclustering analysis, which can be used at the basis of a recommender system for educational orientation of Russian School graduates. The first algorithm was designed to help students make a choice between different university faculties when some of their preference…
We provide scientific foundations for athletic performance prediction on an individual level, exposing the phenomenology of individual athletic running performance in the form of a low-rank model dominated by an individual power law. We present, evaluate, and compare a selection of methods for prediction of individual …
Survey on non-positively curved cube complexes and geometric group theory.
Lectures given at the summer school on Algebraic Groups, Goettingen, June 27 - July 15 2005
Golden age of mathematical finance in the late 20th century.
Preschool attendance correlates with lower developmental vulnerabilities in Queensland, Australia.
We investigate the dynamical behavior in the large scale region of non-equilibrium systems, by employing data on the assessed value of land in 1983 -- 2006 Japan. In the system we find the detailed quasi-balance, which has the symmetry: x_1 -> a {x_2}^θ (x_1 and x_2 are two successive land prices). By using the detaile…
Lecture notes for a minicourse to given in the XVII Brazilian School of Geometry, UFAM (Amazonas), Brazil, July 2012.
This is a set of lecture notes for a course given at the 2005 Summer School in Poisson Geometry held at ICTP-Trieste.
Deep learning's success is puzzling from a statistical perspective.
Posing Kepler's problem of motion around a fixed "sun" requires the geometric mechanician to choose a metric and a Laplacian. The metric provides the kinetic energy. The fundamental solution to the Laplacian (with delta source at the "sun") provides the potential energy. Posing Kepler's three laws (with input from Gali…
Improved incremental sequence classification with temporal consistency.
New principles needed for scaling large language models, challenging traditional regularization methods.
The source of these notes is a series of lectures given at the CIMPA's summer school "Recent Topics in Geometric Analysis".
Lecture notes from the Third International School on Geometry and Physics at the Centre de Recerca Matematica in Barcelona, March 26--30, 2012.
Financial losses follow earthquake-like patterns, study finds.
The paper reviews methods for estimating individual treatment effects using non-parametric regression models.
This Chapter is written for the Festschrift celebrating the 70th birthday of the distinguished economist Duncan Foley from the New School for Social Research in New York. This Chapter reviews applications of statistical physics methods, such as the principle of entropy maximization, to the probability distributions of …
Lecture notes for the minicourse "Holonomy Groups in Riemannian geometry", a part of the XVII Brazilian School of Geometry, to be held at UFAM (Amazonas, Brazil), in July of 2012.
Urban economies follow universal scaling laws over time.
These are notes from the lecture of Devavrat Shah given at the autumn school "Statistical Physics, Optimization, Inference, and Message-Passing Algorithms", that took place in Les Houches, France from Monday September 30th, 2013, till Friday October 11th, 2013. The school was organized by Florent Krzakala from UPMC & E…
New models explain heavy-tailed behavior in neural networks.
These notes from the 2014 summer school Quantum Topology at the CIRM in Luminy attempt to provide a rough guide to a selection of developments in Khovanov homology over the last fifteen years.
This is a survey of recent contributions to the area of special Kaehler geometry. It is based on lectures given at the 21st Winter School on Geometry and Physics held in Srni in January 2001.
MC-LSTM extends LSTM to conserve mass in neural networks.
These are lecture notes from a series of lectures at the SMF summer school on "Geometric and Quantum Topology in Dimension 3", June 2014. The focus is on Heegaard Floer homology from the perspective of sutured Floer homology.
These notes have been prepared as reading material for the mini-course that the author gave at IMS, National University of Singapore, as part of the "Summer school on the moduli space of Higgs bundles".