Bi-LSTM classifies legal documents for Brazil's supreme court.
problem Clogging of Brazil's supreme court due to high volume of lawsuit cases.
method Used a Bidirectional Long Short-Term Memory (Bi-LSTM) network.
result Successfully classified legal documents for efficient case allocation.
What happens when the Supreme Court of the United States decides a case impacting one or more publicly-traded firms? While many have observed anecdotal evidence linking decisions or oral arguments to abnormal stock returns, few have rigorously or systematically investigated the behavior of equities around Supreme Court…
Successful attempts to predict judges' votes shed light into how legal decisions are made and, ultimately, into the behavior and evolution of the judiciary. Here, we investigate to what extent it is possible to make predictions of a justice's vote based on the other justices' votes in the same case. For our predictions…
Algorithm beats sports betting markets, showing inefficiencies.
problem Inefficiencies in sports betting markets.
method Created a betting algorithm using a novel dataset and win probability model.
result Above market returns for various sports betting markets.
We present the Bayesian Echo Chamber, a new Bayesian generative model for social interaction data. By modeling the evolution of people's language usage over time, this model discovers latent influence relationships between them. Unlike previous work on inferring influence, which has primarily focused on simple temporal…
Study finds managers' tenure and education influence their choice between in-court and out-of-court restructuring.
problem Exploring managers' characteristics and their impact on restructuring decisions.
method Empirical investigation using upper echelons theory and data from 342 managers of French firms.
result Managers with longer tenure and higher education levels prefer private restructuring over court involvement.
Case Law has a significant impact on the proceedings of legal cases. Therefore, the information that can be obtained from previous court cases is valuable to lawyers and other legal officials when performing their duties. This paper describes a methodology of applying discourse relations between sentences when processi…
Paper presents datasets from European Court of Human Rights judgments for classification studies.
problem Lack of accessible and reproducible datasets for legal judgments.
method Automated open-source scripts for data collection and feature transformation; experimental campaign on machine learning algorithms.
result Consistently good accuracy (75.86% - 98.32%) across binary datasets, with an average accuracy of 96.45%.
Study online RL with mismatched dynamics, achieving sublinear regret.
problem Exploration challenges in online RL with mismatched training and deployment dynamics.
method Introduce supremal visitation ratio, propose efficient algorithm with f-divergence. result Achieves sublinear regret in online RMDPs with optimal dependence on supremal visitation ratio and interaction episodes.
Robust learning method combines kernel smoothing and robust optimization.
problem Certifying robustness against distribution shifts in machine learning models.
method Adapting integral operator using supremal convolution for robustness, leveraging optimal transport.
result The method provides theoretical guarantees for certified robustness and competitive performance.
Researchers predict NBA player salaries using machine learning, avoiding overfitting.
problem Predicting NBA player salaries based on performance statistics.
method Selected important determinants, used Random Forest machine learning, avoided overfitting.
result Very satisfactory salary predictions identified for important factors.
Study on supply chain networks using wire transfers in Brazil.
problem Understanding economic integration and specialization in Brazilian cities.
method Constructed a directed and weighted network of wire transfers between cities, analyzed centrality measures, and used econometric analysis.
result Disassortative mixing pattern in trade network, stronger after recession, and impact of court efficiency on economic transactions.
Machine learning predicts ECHR judgments on human rights violations.
problem Predicting the outcome of ECHR judgments on human rights violations.
method Auto-sklearn for model selection, N-grams, word embeddings, doc2vec, echr2vec for feature extraction, cross-validation for accuracy assessment.
result Features from echr2vec embedding provided the highest cross-validation accuracy for 5 Articles, overall test accuracy was 68.83%.
A new ranking model uses nonnegative matrix factorization for tennis players.
problem Modeling latent variables influencing tennis player performance.
method Combines Bradley-Terry-Luce model with nonnegative matrix factorization.
result Model identifies surface type as key determinant of male player performance.
Formulates LGFO to measure fair ML systems using legal signals.
problem Formally incompatible measures of unfairness in ML systems.
method Uses legal signals to measure social cost of unfairness.
result LGFO aligns with societal view of unfairness.
Research shows higher damages may encourage more disclosure in corporate disputes.
problem How to resolve disputes over undisclosed material events in a way that encourages voluntary disclosure.
method Dynamic continuous-time model of management's equilibrium disclosure decision.
result Increased damages may lead to an endogenous increase in voluntary disclosure.
The study constructs and shows isotopy of high-dimensional Legendrian spheres.
problem Understanding Legendrian spheres in contact manifolds of any dimension.
method Three Legendrian sphere constructions using open books and a doubling procedure.
result These constructions are isotopic to the Legendrian unknot.
Given a positive function u∈W1,n, we define its John-Nirenberg radius at point x to be the supreme of the radius such that ∫Bt∣∇logu∣n<ε0n when n>2, and ∫Bt∣∇u∣2<ε02 when n=2. We will show that for a collapsing sequence in a fixed conformal class under some curvature c…
New method for decomposing manifolds into 1-handlebodies.
problem Decomposing manifolds into 1-handlebodies.
method Multisections of surface bundles and fiber bundles over the circle.
result Multisections exist for surface bundles and fiber bundles over the circle.
Study of 3-manifolds in 5-sphere using bridge decompositions.
problem Understanding embeddings of 3-manifolds in 5-sphere.
method Introduce and study bridge decompositions, use multisections of 5-manifolds.
result Every embedded 3-manifold admits a bridge decomposition.
Many natural systems, such as neurons firing in the brain or basketball teams traversing a court, give rise to time series data with complex, nonlinear dynamics. We can gain insight into these systems by decomposing the data into segments that are each explained by simpler dynamic units. Building on switching linear dy…
Protocol minimizes disclosure in classification tasks.
problem Ensuring minimal disclosure in classification protocols.
method Developed a protocol for multi-party classification that minimizes non-responsive document disclosure.
result Guarantees minimal disclosure of non-responsive documents.
Unified treatment of reinforcement learning via convex duality.
problem Applying Fenchel-Rockafellar duality to reinforcement learning.
method Unified derivation of various RL settings using convex duality.
result Ability to perform policy evaluation and on-policy policy gradient with offline data.
Two trees in the boundary of outer space are said to be \emph{primitive-equivalent} whenever their translation length functions are equal in restriction to the set of primitive elements of FN. We give an explicit description of this equivalence relation, showing in particular that it is nontrivial. This question is …
Functor connects sheaves on Lagrangian cobordisms, proving equivalence and action decreasing properties.
problem Understanding sheaf equivalences and actions on Lagrangian cobordisms.
method Analyzing sheaf quantizations and Legendrian lifts, proving functorial properties.
result Lagrangian cobordism functor is action decreasing and Morita equivalent to sheaf categories of Legendrians.
The paper constructs multisections for m-spun 3-manifolds in higher dimensions.
problem Finding multisections for higher-dimensional manifolds.
method Extending the concept of spun 3-manifolds to higher dimensions, constructing multisections and diagrams.
result Infinitely many examples of non-diffeomorphic multisected manifolds in all dimensions.
New SGD analysis for nonconvex optimization finds optimal rates.
problem Optimizing nonconvex functions in machine learning.
method Introduces a new expected smoothness assumption and analyzes SGD convergence rates.
result Optimal convergence rates for nonconvex smooth functions and global solutions under certain conditions.
Novel RL-based NPG improves multi-objective NAS efficiency and performance.
problem Discovering optimal neural architectures with multiple conflicting objectives.
method Non-stationary policy gradient with adaptive reward functions and shared model.
result Framework efficiently approximates full Pareto front and achieves superior performance.
ERM struggles with synthetic data, but some algorithms can still learn correctly.
problem Learning from a mix of natural and synthetic data.
method Modeling the scenario as a sequence of learning tasks with oblivious algorithms, studying ERM and its limitations.
result ERM converges to the true mean but is outperformed by weighted algorithms. ERM does not always converge in the PAC setting, but there are algorithms capable of learning the correct hypothesis.
Classifies treatment responders using monotonic causal effects.
problem Predicting treatment response based on features and past examples.
method Developed discriminative and generative algorithms leveraging monotonicity.
result New algorithms outperform standard benchmarks in responder classification.
For a Hamiltonian K∈C2(RN×n) and a map u:Ω⊆Rn⟶RN, we consider the supremal functional \[ \label{1} \tag{1} E_\infty (u,Ω) \ :=\ \big\|K(Du)\big\|_{L^\infty(Ω)} . \] The "Euler-Lagrange" PDE associated to \eqref{1} is the quasilinear system \[ \lab…
New algorithm guarantees optimal convergence rate for stochastic optimization.
problem Optimal convergence rate for stochastic optimization algorithms.
method Regularized versions of Minimization by Incremental Surrogate Optimization (MISO) with arbitrary recurrent data sampling.
result Expected optimality gap converges at O(n−1/2) under general recurrent sampling schemes. Paper uses GAN to generate synthetic seismic data for earthquake detection.
problem Challenges in detecting earthquake events from seismic time series data.
method Generative Adversarial Network (GAN) to generate synthetic seismic data.
result GAN-generated synthetic seismic data significantly improves earthquake detection accuracy.
This research adapts superpixels for Shapley value computation in DNA profile classification.
problem Efficiently computing Shapley values for large, multidimensional time-series data.
method Adapting the concept of superpixels to streamline Shapley value computation for time-series-like data.
result Realistic, accurate, and fast computation of Shapley values for DNA profile classification.
Surface parameterizations and registrations are important in computer graphics and imaging, where 1-1 correspondences between meshes are computed. In practice, surface maps are usually represented and stored as 3D coordinates each vertex is mapped to, which often requires lots of storage memory. This causes inconvenien…
Stablecoins offer efficient settlement but externalize costs and risks.
problem Comparing stablecoins to card networks in retail payments.
method Unified analytical framework (CLEAR) across five dimensions.
result Stablecoins are advantageous in closed-loop and high-friction contexts but structurally disadvantaged as open-loop instruments.
Big data comes in various ways, types, shapes, forms and sizes. Indeed, almost all areas of science, technology, medicine, public health, economics, business, linguistics and social science are bombarded by ever increasing flows of data begging to analyzed efficiently and effectively. In this paper, we propose a rough …
Boosted DT classifiers become DP with new calibrated loss.
problem Making boosted DT classifiers differentially private.
method Crafted Mα-loss and objective calibration. result Significantly outperforms random forests in DP settings.
Proposes an online method for solving non-convex DRO with KL regularization.
problem Solving distributionally robust optimization with non-convex objectives.
method Practical online stochastic methods for DRO with KL regularization, avoiding high-dimensional dual variables and online learning issues.
result Empirical studies show significant speedup and efficiency in training deep learning models.
Ancestry improves genealogy search results by ranking diverse record types.
problem Ranking diverse genealogy records equitably from various sources.
method Customized Coordinate Ascent, Stochastic Search, Normalized Cumulative Entropy.
result Demonstrated effectiveness of algorithms in improving relevance and diversity.
Corporate governance struggles to curb fraud in a globalized economy.
problem Lack of effective international regulations against corporate fraud.
method Analyzes historical economic crises and the role of corporate governance.
result Corporate governance is insufficient to prevent large business fraud.
EF21 improves convergence in distributed machine learning models.
problem Improving convergence in distributed machine learning models.
method Proposes EF21, a new error feedback mechanism.
result EF21 achieves a fast O(1/T) convergence rate for smooth nonconvex problems. New tail inequalities for sums of random matrices without matrix-dimension terms.
problem Tail behavior of matrix functions in high-dimensional settings.
method Developed new tail inequalities for matrix sums, independent of matrix dimension.
result Tail inequalities for various matrix functions without matrix-dimension terms.
Develops a framework to estimate NBA player salary ROI.
problem Measuring the relative return of player salaries in NBA.
method Five-part framework: GCP measure, SGV calculation, cash flow series, ROI calculation.
result Illustrates framework with 2022-2023 NBA data, showing top and bottom performers.