New methods for efficiently ranking unknown response surfaces.
problem Efficiently finding the best response surface among multiple unknown ones.
method Sequential design methods using stepwise uncertainty reduction and posterior classification complexity.
result Effective design heuristics for continuous-input response surface ranking.
Deep learning ranks response surfaces for optimal stopping problems in finance.
problem Ranking response surfaces in stochastic control problems.
method Reformulate as image segmentation problem and apply deep learning algorithms.
result Deep learning provides an efficient method for solving optimal stopping problems.
This work accelerates uncertainty propagation in DNNs using active subspace.
problem Challenges in propagating uncertainty in DNN predictions from real-world data.
method Gradient-based active subspace method and response surface technique.
result Efficient uncertainty propagation in DNN predictions at low computational cost.
RLGP model improves robustness and accuracy for discontinuous response surfaces.
problem Challenges in modeling abrupt jumps and discontinuities in response surfaces.
method Integrates adaptive nearest-neighbor selection with robustification mechanism.
result Consistently delivers high predictive accuracy and robustness in higher dimensions.
Study optimizes CANN for actuarial tasks using RSM.
problem Optimizing hyperparameters for neural networks in actuarial science.
method Factorial design and response surface methodology (RSM).
result Reduced hyperparameter optimization from 288 to 188, achieving near-optimal performance.
Study explores kinematics of surfaces under metric restrictions.
problem Understanding the kinematics of surfaces under metric constraints.
method Analyzed three energy contents: stretching, drilling, and bending.
result Metric restrictions can hinder the elastic response of a shell.
A new framework interprets machine learning models using Gaussian processes.
problem Interpreting complex machine learning models.
method Gaussian process metamodeling to capture response surfaces.
result Maximizing likelihood function for variable importance.
Aims to optimize complex multivariate systems with constraints.
problem Optimizing force-field systems in physics with large-scale simulations.
method Combines machine learning and experimental design to find feasible input combinations.
result Locates multiple good regions in the input space.
Modeling high-dimensional surfaces for toxicity testing using tensor product basis functions.
problem Characterizing complex high-dimensional surfaces from high-throughput toxicity testing data.
method Developed a novel Bayesian additive adaptive basis tensor product model.
result Model accurately predicts dose-responses for untested chemicals.
ROD reconstructs conditional mean surfaces from observational data, invariant to term order.
problem Regression estimates from observational data can be biased by multicollinearity and term order.
method Retrospective Orthogonal Design (ROD) reconstructs surfaces on a probability-balanced lattice, preserving observed and completing unsupported cells.
result ROD outperformed polynomial regression across various data-generating processes, achieving high out-of-sample R2. Analytic formulae for point vortex dynamics on surfaces with symmetry.
problem Understanding point vortex behavior on surfaces with continuous symmetry.
method Derived analytic formulae for Green and Robin functions on surfaces with hydrodynamic Killing vector fields.
result Unified tool for detailed studies of point vortex dynamics and Euler-Arnold flows on surfaces with continuous symmetry.
A short proof for curve lengths on hyperbolic surfaces.
problem Proving a theorem about curve lengths on hyperbolic surfaces.
method Presented a concise proof for the theorem.
result A pair of curves has length at least half the perimeter of a specific polygon.
New framework reveals limits of flexible, periodic thin surfaces.
problem Understanding the mechanical behavior of thin, periodic surfaces.
method Developed a duality between surface rotations and in-plane stresses.
result Exactly three out of six possible strain states are isometries.
Any given surface of revolution embedded in Euclidean three-space can always be perturbed by arbitrarily small ambient isotopies as to admit highly nontrivial vector fields inducing infinitesimal deformations. For this matter Morse Theory is used, clarifying and giving a general response of a problem started with an id…
HierGP improves emulator efficiency for sparse, structured data.
problem Sparse, structured data in expensive simulations.
method Hierarchical shrinkage GP framework with cumulative shrinkage priors.
result HierGP identifies structured sparse features from limited data.
We study various aspects related to boundary regularity of complete properly embedded Willmore surfaces in H3, particularly those related to assumptions on boundedness or smallness of a certain weighted version of the Willmore energy. We prove, in particular, that small energy controls C1 boundary regularity. We examin…
Clarifies structures in link homology theories using Frobenius extensions.
problem Understanding key flavors of equivariant SL(2) link homology theories.
method Provides a convenient scheme and diagrammatics for Frobenius extensions.
result Proposes a setup for working over non-degenerate base rings.
LOOCV is often useful for analyzing small, structured experimental designs.
problem The effectiveness of cross-validation in analyzing designed experiments.
method Empirical study comparing LOOCV and other model selection methods.
result LOOCV is often useful in the analysis of small, structured experimental designs.
We are focusing on bound constrained global optimization problems, whose objective functions are computationally expensive black-box functions and have multiple local minima. The recently popular Metric Stochastic Response Surface (MSRS) algorithm proposed by \cite{Regis2007SRBF} based on adaptive or sequential learnin…
Study shows infinite manifold types for every group.
problem Finding manifold types for every finite group.
method Proved existence of infinitely many compact complex hyperbolic 2-manifolds.
result For every finite group, there are infinitely many isomorphism classes of compact complex hyperbolic 2-manifolds with automorphism group isomorphic to the group.
A new method for Gaussian Processes handles mixed continuous and categorical inputs.
problem Modeling cross-correlations between continuous and categorical data.
method Low-Rank Correlation (LRC) method for Gaussian Processes with flexible rank approximation.
result LRC outperforms existing methods in estimating cross-correlations and predicting response surfaces.
In this paper, we discuss a one parameter family of complex Born-Infeld solitons arising from a one parameter family of minimal surfaces. The process enables us to generate a new solution of the B-I equation from a given complex solution of a special type (which are abundant). We illustrate this with many examples. We …
New algorithm tackles high-dimensional simulation optimization, converging efficiently.
problem High-dimensional simulation optimization challenges.
method Sparse grid experimental design combined with kernel ridge regression using Brownian field kernel, followed by expected improvement strategy.
result Established upper bounds on convergence rate, demonstrating superior performance in practice.
PARyOpt optimizes functions asynchronously, reducing wall clock time.
problem Efficiently optimizing functions on distributed systems with asynchronous evaluations.
method Parallel asynchronous Bayesian optimization.
result Reduces total optimization time for various test problems.
The paper analyzes defects on structured surfaces and calculates stress and shape.
problem Analyzing defects on structured surfaces and their effects on stress and shape.
method Classified and quantified defects, derived strain incompatibility relations, and applied to shells.
result Determined internal stress field and deformed shape for shells with defects.
Study on cross-responses in correlated financial markets, distinguishing active and passive responses.
problem Understanding price responses across different stocks in correlated financial markets.
method Performed different averages to identify active and passive cross-responses, analyzed their characteristics and compared with self-responses.
result Active cross-responses have longer response periods compared to passive cross-responses.
Study on combinatorial k-systoles on surfaces, showing growth in intersection numbers.
problem Understanding the intersection numbers of closed curves on surfaces.
method Analyzing combinatorial k-systoles on punctured tori and pairs of pants. result The maximal intersection number of combinatorial k-systoles grows like k and approaches infinity as k increases. Neural nets detect alarming student responses for quick review.
problem Identifying alarming student responses in online assessments.
method Developed neural network models to flag potentially concerning responses.
result Neural nets can flag alarming responses more efficiently than manual review.
Study price responses in correlated financial markets, finding transient impacts and sector-specific differences.
problem Understanding price responses in correlated financial markets.
method Empirical investigation of stock price responses to trades of other stocks, distinguishing active and passive responses.
result Price responses are transient, with active and passive responses showing different characteristic time lags.
FaIRGP model improves climate emulation with physical interpretability.
problem Lack of physical interpretability in data-driven emulators.
method Bayesian approach to a data-driven emulator of energy balance equations.
result Demonstrates skillful emulation of global and spatial surface temperatures.
Study of discrete period matrices on embedded graphs, relating to Riemann surfaces.
problem Understanding discrete conformal structures on surfaces via period matrices.
method Combinatorial interpretation of period matrices, using homological quasi-trees and Laplacian determinants.
result Derived a combinatorial analogue of the Weil-Petersson potential and related it to homological quasi-trees.
Proposes a new method for multivariate functional regression.
problem Multivariate functional regression with complex relationships.
method Nested reduced-rank regularization (NRRR) approach.
result Consistent and effective in fitting multivariate functional regression models.
The paper proposes a framework to detect student misconceptions from textual responses.
problem Detecting misconceptions from students' responses to open-response questions.
method A natural language processing-based probabilistic model for detecting common misconceptions.
result The proposed framework excels at classifying and detecting common misconceptions.
A new adaptive kriging method improves binary classification of mechanical problems.
problem Efficient binary classification of mechanical problems with high fluctuation.
method Monte Carlo-intersite Voronoi (MiVor) adaptive scheme for regression surrogate model.
result The MiVor algorithm provides accurate binary classification with fewer observation points for highly fluctuating response surfaces.
Study evaluates different price response definitions for NASDAQ stocks.
problem Understanding the long-lasting effects of trading activity on stock prices.
method Examined two different price response implementations for NASDAQ Trades and Quotes (TAQ) data.
result Results are qualitatively the same for two different time scale definitions, but response can vary by up to a factor of two.
Dual-decoder model generates responses with targeted sentiment.
problem Generating human-like responses with specific sentiment.
method Simple dual-decoder model with two sentiment decoders connected to one encoder.
result Significant performance gain in sentiment accuracy and word diversity.
The paper learns compact implicit surface maps from streaming data using an ensemble of sparse Gaussian processes.
problem Creating compact and accurate implicit surface maps from streaming range data.
method An ensemble of sparse Gaussian process experts, incrementally adjusted, trades-off between model complexity and prediction error.
result The approach learns compact and accurate implicit surface models comparable to or better than exact GP regression with subsampled data.
Model decodes sounds from neural responses, achieving 70% accuracy.
problem Decoding natural sounds from neural recordings.
method Kernel convolution model to decode acoustic features from neural responses.
result Model accurately distinguishes between sounds with 70% accuracy.
Examines cross-stock price responses in correlated financial markets.
problem Understanding the impact of trades on prices across different stocks.
method Empirical investigation of cross-responses in a correlated market.
result Cross-stock price responses are transient, not permanent.
Interpretable text-response modelling for structured outcomes
problem Predicting structured responses alongside textual data
method Joint non-negative matrix factorisation and binomial regression
result Recovering stable response-relevant textual signals
LaRT models LLMs' response accuracy and CoT length to evaluate reasoning ability and speed.
problem Valid evaluation of Large Language Models (LLMs) via response accuracy and chain-of-thought length.
method Introduces Latency-Response Theory (LaRT) to jointly model response accuracy and CoT length using latent ability and latent speed.
result LaRT yields higher estimation accuracy and shorter confidence intervals for latent traits compared to IRT.
New methods improve accuracy in predicting complex systems.
problem Improving accuracy in predicting complex physical systems from simulators.
method Proposes two new methods of design approaches that sequentially select input settings.
result Demonstrates effectiveness of the proposed methods through numerical examples.
Bayesian priors improve estimation of complex response functions in dynamic medical imaging.
problem Estimating complex response functions in dynamic medical imaging.
method Non-parametric Bayesian priors for blind source separation and deconvolution.
result Flexible non-parametric priors improve estimation of response functions in both synthetic and real datasets.
New method handles correlated responses and interaction effects in multi-response regression.
problem Handling correlated responses and interaction effects in multi-response regression.
method MADMMplasso, an ADMM-based approach for multi-response regression with overlapping groups and interaction effects.
result The proposed method outperforms in prediction and variable selection for correlated responses and interaction effects.
New method for explaining dialogue response generation models.
problem Interpreting sequence generation models, especially dialogue response generation.
method Local Explanation of Response Generation (LERG) method.
result LERG improves dialogue response generation explanations compared to existing methods.
PEER tackles multi-response regression with incomplete outcomes efficiently.
problem Challenges in estimating, predicting, and computing with large-scale multi-response regression and incomplete outcomes.
method PEER converts multi-response regression into parallel univariate-response regressions.
result PEER achieves consistency in estimation, prediction, and variable selection.
Study analyzes price response and spread impact in foreign exchange markets.
problem Understanding deviations from Markovian behavior in foreign exchange markets.
method Detailed large-scale data analysis of price response functions for different years and time scales, using pip bid-ask spread definition.
result Large pip spreads significantly impact price response in foreign exchange markets.
Study price responsiveness in electricity demand using empirical data.
problem Limited effectiveness of classical economic theories in real-time retail pricing.
method Dynamic modeling of hybrid Hammerstein model with delay and linear ARX model.
result Electricity consumption has distinct responses to moderate and high prices with a time delay.