A new algorithm estimates and controls FDR for PC algorithm edges.
problem Estimating and controlling FDR for PC algorithm edges.
method PC-p algorithm using edge-specific p-values and Benjamini-Yekutieli FDR procedure.
result PC-p yields more accurate FDR estimation and control.
Study tests five popular trading signal families and finds four refuted, one inconclusive, and one not refuted.
problem Testing the viability of five popular trading signal families for generating a positive edge.
method Statistical edge testing, economic viability assessment, and finite-bankroll survival under leverage using exposure-matched benchmarks, stationary-bootstrap confidence intervals, and hierarchical Benjamini-Yekutieli control.
result Four out of five signal families are refuted, one is inconclusive, and one is not refuted.
Optimal learning procedure for arbitrary function classes.
problem Learning arbitrary function classes without structural properties.
method Unrestricted learning procedure that selects functions outside given class.
result Optimal sample complexity for arbitrary function classes.
The need for parameter estimation with massive datasets has reinvigorated interest in stochastic optimization and iterative estimation procedures. Stochastic approximations are at the forefront of this recent development as they yield procedures that are simple, general, and fast. However, standard stochastic approxima…
AI system synthesizes chemical plant operation procedures for efficiency and stability.
problem Developing efficient and stable operation procedures for complex chemical plants.
method Integrates automated reasoning, deep reinforcement learning, and dynamic simulation with external knowledge.
result Synthesized procedure achieves faster recovery from malfunctions compared to standard PID control.
We describe a procedure which verifies that a group given by generators and relators is word-hyperbolic. This procedure always works with a group which is word-hyperbolic, provided there is sufficient memory and time devoted to the problem. If the group is not word-hyperbolic, the procedure continues indefinitely. We a…
New method outperforms standard procedures in heavy-tailed problems.
problem Regression function estimation under heavy-tailed conditions.
method Regularized risk minimization procedure based on median-of-means tournaments.
result The new procedure achieves near optimal accuracy and confidence in heavy-tailed problems.
Myopic procedures are shown to be asymptotically optimal in ranking and selection problems.
problem Selecting the best design from a set with unknown mean performance.
method Myopic procedures that iteratively improve an approximation of the objective measure.
result Myopic procedures satisfy optimality conditions of ranking and selection problems.
Several authors have pointed out the connection between Barbilian's metric introduced in 1934 and the recent study of Apollonian metrics. We provide examples of various distances that can be obtained by Barbilian's metrization procedure and we discuss the relation between this metrization procedure and important Rieman…
Biclustering, the process of simultaneously clustering the rows and columns of a data matrix, is a popular and effective tool for finding structure in a high-dimensional dataset. Many biclustering procedures appear to work well in practice, but most do not have associated consistency guarantees. To address this shortco…
ARK improves knockoffs robustness to feature distribution misspecification.
problem Robustness of knockoffs inference to misspecified feature distributions.
method Coupling approximate knockoffs with model-X knockoffs to achieve FDR and FWER control.
result The approximate knockoffs procedure can control FDR and FWER asymptotically.
Deep learning predicts procedures from diagnoses in EHRs.
problem Manual procedure coding is time-consuming and error-prone.
method Multi-label classification using distributed representations.
result Model outperforms existing methods with high recall.
A new procedure, called DDa-procedure, is developed to solve the problem of classifying d-dimensional objects into q >= 2 classes. The procedure is completely nonparametric; it uses q-dimensional depth plots and a very efficient algorithm for discrimination analysis in the depth space [0,1]^q. Specifically, the depth i…
Investigation of the market graph attracts a growing attention in market network analysis. One of the important problem connected with market graph is to identify it from observations. Traditional way for the market graph identification is to use a simple procedure based on statistical estimations of Pearson correlatio…
A new method calibrates forecasts without sacrificing expertise.
problem Forecasters' calibration scores can be manipulated to appear expert.
method Deterministic and stochastic online procedures to calibrate forecasts.
result Calibration can be achieved without losing expertise.
Model shows IRS procedure for health insurance tax credits can diverge, proposing a new bisection method.
problem IRS procedure for calculating health insurance tax credits diverges for some self-employed taxpayers.
method Proposed a bisection procedure to calculate appropriate premium tax credits for tax returns.
result The bisection procedure can calculate appropriate premium tax credits for a model of simple tax returns.
Procedure groups nonparametric regression curves automatically.
problem Determining groups of nonparametric regression curves when curves are numerous.
method Automatic selection of group number through testing procedure.
result Groups of nonparametric regression curves exist in tunnel geometry.
Procgen Benchmark uses procedurally generated games to test reinforcement learning.
problem Lack of diverse and high-quality training environments for reinforcement learning.
method Developed 16 procedurally generated game-like environments and used them to benchmark reinforcement learning.
result Procedurally generated environments are essential for training and evaluating reinforcement learning agents.
PLOTS learns procedural actions from observed sequences, up to 100x faster.
problem Learning procedural actions from observed sequences efficiently.
method Exploits subtask structure to incrementally build action plans, optimistically explores actions.
result Explicit procedural learning is 100x faster than policy-gradient methods and model-based approaches.
Let $\cF$ be a set of M classification procedures with values in [−1,1]. Given a loss function, we want to construct a procedure which mimics at the best possible rate the best procedure in $\cF$. This fastest rate is called optimal rate of aggregation. Considering a continuous scale of loss functions with various …
We develop a mixture procedure for multi-sensor systems to monitor data streams for a change-point that causes a gradual degradation to a subset of the streams. Observations are assumed to be initially normal random variables with known constant means and variances. After the change-point, observations in the subset wi…
The paper describes a method to infer the signal-to-noise ratio in portfolio optimization.
problem Estimating the signal-to-noise ratio in portfolio optimization problems.
method A statistic similar to the Sharpe Ratio Information Criterion is used for inference.
result The method works well for reasonable sample and asset universe sizes.
Automatically generate inference procedures from models using program transformations.
problem Manual coding of inference algorithms is tedious and error-prone.
method Decompose inference algorithms into reusable transformations and generate inference procedures from models.
result Generated inference procedures are as accurate and fast as other systems.
Project learns to model Capsule Networks' routing procedures for better expressiveness.
problem Limited expressiveness of Capsule Networks' inner routing procedures.
method Proposes two ways to learn the routing procedure as a network parameter.
result Improved expressiveness of Capsule Networks through learned routing procedures.
In this article we give our contribution to the problem of segmentation with plug-in procedures. We give general sufficient conditions under which plug in procedure are efficient. We also give an algorithm that satisfy these conditions. We give an application of the used algorithm to hyperspectral images segmentation. …
EarlyStopping package helps prevent overfitting in iterative learning procedures.
problem Preventing overfitting in iterative learning procedures.
method Early stopping implemented in a Python package.
result Demonstrates how to use the EarlyStopping package to explore implicit regularization.
Two novel procedures track quantiles efficiently using an oracle.
problem Setting step size and tuning parameters for incremental quantile estimators.
method Estimate MSE, decompose into variance and bias, use oracle to select best estimator.
result Efficient quantile tracking with error close to theoretical optimum.
Variable selection plays an important role in the high-dimensional data analysis. However the high-dimensional data often induces the strongly correlated variables problem. In this paper, we propose Elastic Net procedure for partially linear models and prove the group effect of its estimate. By a simulation study, we s…
Desingularizes Einstein metrics with A1 singularities in 4D.
problem Desingularizing Einstein metrics with specific singularities.
method Recursive procedure to desingularize Fuchsian singularities.
result Desingularizations of non degenerate Poincaré-Einstein metrics with A1 singularities remain non degenerate.
New model constructs astronomical catalogs from images efficiently.
problem Building accurate catalogs from large image datasets.
method Generative model with MCMC and VI for inference.
result Variational inference is 1000x faster with similar accuracy.
Generative models create terrain maps from satellite data.
problem Traditional handcrafted algorithms for generating video game terrains.
method Deep generative models trained on satellite imagery.
result Learning and synthesis of terrain maps using GANs.
Boundary properties of hyperbolic groups are invariant under a maximization procedure.
problem Proving boundary properties of hierarchically hyperbolic groups are invariant.
method Proving boundary invariance under a maximization procedure.
result Boundary properties of hierarchically hyperbolic groups are invariant under maximization.
In the present paper we discuss the cabling procedure for the colored HOMFLY polynomial. We describe how it can be used and how one can find all the quantities such as projectors and R-matrices, which are needed in this procedure. The constructed matrix forms of the projectors and the fundamental $\mathcal{…
Proposes cost-sensitive feature selection for SVMs.
problem Asymmetric misclassification costs in feature selection.
method Mathematical optimization-based approach for SVMs.
result Substantial reduction in feature count with desired error rates.
A new procedure aggregates models to predict data from multiple clusters.
problem Predicting data from multiple clusters with different underlying models.
method Three-step procedure: clustering, model fitting, and aggregation.
result The method outperforms existing models in various prediction problems.
The paper analyzes methods for estimating linear functionals from observational data, proving upper bounds and showing optimal procedures.
problem Estimating linear functionals from observational data in causal inference and bandit literature.
method Two-stage procedures that first estimate treatment effect function, then use it to estimate the linear functional.
result Proves non-asymptotic upper bounds on mean-squared error for two-stage procedures and shows instance-dependent optimality.
We introduce a new recursive aggregation procedure called Bernstein Online Aggregation (BOA). The exponential weights include an accuracy term and a second order term that is a proxy of the quadratic variation as in Hazan and Kale (2010). This second term stabilizes the procedure that is optimal in different senses. We…
New procedures connect braid charts, triplane diagrams, and braid movies for knotted surfaces.
problem Understanding the braid index and bridge index of knotted surfaces in 4D.
method Introducing rainbow diagrams and new procedures for passing among triplane diagrams, braid movies, and braid charts.
result Inequalities relating braid index and bridge index of 2-knots are obtained.
Iterative procedures for parameter estimation based on stochastic gradient descent allow the estimation to scale to massive data sets. However, in both theory and practice, they suffer from numerical instability. Moreover, they are statistically inefficient as estimators of the true parameter value. To address these tw…
Proposes a method to ensure low losses across all subpopulations in large datasets.
problem Standard practice of minimizing average loss fails to guarantee low losses across all subpopulations in heterogeneous datasets.
method Convex procedure that controls worst-case performance over all subpopulations of a given size with finite-sample convergence guarantees.
result Empirically, the worst-case procedure learns models that do well against unseen subpopulations.
Procedure estimates modal-sets with consistency guarantees for clustering.
problem Estimating local maxima of densities in noisy data.
method Estimates modal-sets with statistical consistency guarantees.
result Modal-sets can serve to better model dense low-dimensional structures in data.
For the equations of the form y′′=P(x,y)+3Q(x,y)y′+3R(x,y)y′2+S(x,y)y′3 the problem of equivalence in the class of point transformations is considered. Effective procedure for determining the class of point equivalence for the given equation is suggested. This procedure is based on explicit formulas for t…
Machine learning speeds up search procedures for sorted tables.
problem Improving the speed of sorted table search procedures.
method Systematic experimental comparison of efficient implementations with learned counterparts.
result Learned data structures can significantly speed up search procedures.
Optimizes loan recovery timing across various portfolios.
problem Comparing and evaluating bank's loan recovery decision rules.
method Simulation-based expert system considering time value of money and costs.
result Threshold optima exist across different risk scenarios and portfolio compositions.
Concave regularization methods provide natural procedures for sparse recovery. However, they are difficult to analyze in the high dimensional setting. Only recently a few sparse recovery results have been established for some specific local solutions obtained via specialized numerical procedures. Still, the fundamental…
Boosted conformal procedure improves prediction intervals.
problem Enhancing prediction interval properties like coverage and length.
method Gradient boosting to optimize conformity score function.
result Significant improvements in interval length and coverage.
This note explains how to transform Heegaard diagrams into framed link diagrams.
problem No specific problem stated; transformation of diagrams is the focus.
method Explains a procedure to transform Heegaard diagrams into framed link diagrams.
result Demonstrates a method to transform Heegaard diagrams into framed link diagrams.
Gauging procedure constructs lagrangians for carrollian gravity.
problem Constructing lagrangians for carrollian gravity.
method Gauging procedure applied to Klein pairs corresponding to homogeneous spaces.
result Generalizes first-order lagrangians for four-dimensional maximally symmetric carrollian spaces.