Dual-view mixture models cluster users with features and latent behaviors inferred from actions.
problem Clustering users based on features and latent behavioral functions inferred from indirect observations.
method Dual-view mixture models with non-parametric Dirichlet Process for automatic cluster number inference.
result Dual-view models outperform single-view models when one view lacks information.
Investing in high quality firms yields excess returns, contrary to risk or behavioral explanations.
problem Excess returns of quality stocks despite risk and behavioral explanations.
method Investigated two explanations: risk and behavioral views; provided novel evidence for the behavioral view.
result Excess returns of quality stocks are not due to risk, but due to systematic underestimation by analysts.
Revisits behavioral finance option pricing model to align with rational asset pricing theory.
problem Inconsistency between behavioral finance and rational asset pricing models in option pricing.
method Introduces arbitrage transaction costs to modify the behavioral finance option pricing formula.
result Modifies behavioral finance option pricing formula to be consistent with rational asset pricing theory.
Researchers compute Hessian of Ding functionals and analyze its convexity and asymptotic behavior.
problem Analyzing the convexity and asymptotic behavior of quantized Ding functionals.
method Computed the Hessian of quantized Ding functionals using projective geometry and Berezin-Toeplitz quantization.
result Elementary proof of convexity of quantized Ding functionals along Bergman geodesics.
Model captures neural activity related to behavior while separating internal computations.
problem Capturing neural activity related to behavior from complex brain recordings.
method Behavior-decomposed linear dynamical systems (b-dLDS) model.
result Improves over state-of-the-art models in disentangling behavior-related dynamics.
Deep learning improves recommendation systems for marketplaces.
problem Challenges in matrix factorization for marketplaces.
method Hybrid recommender system combining user-generated contents and user behavior data.
result Five lessons learned from deep learning experiments.
Paper proposes a tensor model for clustering noisy multi-view data.
problem Clustering noisy multi-view data with non-uniform variances.
method Nested matrix-tensor model for best rank-one approximation.
result Theoretical results predict the exact accuracy of clustering.
Global study of capillarity equation solutions.
problem Understanding solutions to capillarity equation globally.
method Global analysis without boundary conditions.
result Characterization of solutions' constraints.
This paper analyzes multi-view learning using information theory to improve generalization.
problem Lack of theoretical understanding of multi-view learning's generalization behavior.
method Developed information-theoretic generalization bounds for multi-view learning.
result Capturing both consensus and complementary information maximizes representation disentanglement.
Bayesian market views improve asset allocation performance.
problem Leveraging public mood for trusted and interpretable asset allocation.
method Formalize public mood into market views, use Bayesian asset allocation model, train neural models.
result Formalized market views increase portfolio profitability by 5-10% annually.
Deeper quantum circuits can improve performance on unseen data, contrary to traditional views.
problem Understanding scaling behavior of parameterized quantum circuits and their generalization.
method Gradient-based PQCs, add-one-in perturbation techniques, spectral properties of random matrices.
result Gradient-based PQCs can exhibit improved performance on unseen data as model size increases, displaying double descent behavior.
Derives option pricing formulas consistent with rational asset pricing theory.
problem Existing behavioral finance option pricing formulas allow arbitrage opportunities.
method Introduces transaction costs to offset arbitrage opportunities.
result Derives formulas consistent with rational dynamic asset pricing theory.
Proposes a multi-view architecture for drug-target interaction prediction.
problem Representing compound-target pairs in deep learning models.
method Integrates differentiable and predefined molecular descriptors using an adversarial multi-view architecture.
result Demonstrates potential of the proposed approach on clinically relevant datasets.
We derive a class of macroscopic differential equations that describe collective adaptation, starting from a discrete-time stochastic microscopic model. The behavior of each agent is a dynamic balance between adaptation that locally achieves the best action and memory loss that leads to randomized behavior. We show tha…
This paper reveals periodic behavior in neural network training with BN and weight decay.
problem Understanding the dynamics of neural network training with BN and weight decay.
method Rigorous investigation of empirical and theoretical mechanisms.
result Periodic behavior in training is a generalization of previously opposing perspectives.
Deep networks show less disorder and more monotonic behavior.
problem Understanding the disorder and monotonicity in deep neural networks.
method Computing frustration and analyzing near-monotonicity in signed graphs of deep networks.
result Deep networks exhibit less disorder and more monotonic behavior than expected.
The paper extends a formula linking surface curvature to projection invariants.
problem Investigating invariants of projected surface curves.
method Introduced invariants of plane curves from surface projections; extended d'Ocagne formula.
result Extended d'Ocagne formula connects surface curvature with projection behavior.
We study the J-flow from the point of view of an algebro-geometric stability condition. In terms of this we give a lower bound for the natural associated energy functional, and we show that the blowup behavior found by Fang-Lai is reflected by the optimal destabilizer. Finally we prove a general existence result on com…
Podcast recommendations improved by analyzing user listening paths.
problem Challenges in recommending podcasts effectively.
method Analyzes user listening paths as sequential trajectories for recommendations.
result 450% increase in effectiveness over baseline.
apk2vec builds profiles of Android apps using multiple views, outperforming existing methods.
problem Building comprehensive behavior profiles of Android apps for better analytics.
method Semi-supervised multi-view representation learning combining RL and feature hashing.
result apk2vec's profiles significantly outperform state-of-the-art techniques in app analytics tasks.
The paper uses KKT conditions to reveal new insights into SVM behavior.
problem Understanding SVM behavior and tuning.
method Using Karush-Kuhn-Tucker conditions to explore SVM connections with other classifiers.
result SVM can be seen as a cropped version of mean difference and maximal data piling direction classifiers.
Paper proposes a two-stage ranking for personalized TV recommendations.
problem Improving TV recommendation accuracy and efficiency.
method First, identifies potential candidates using user viewing patterns. Then, ranks them based on user preferences and program textual information.
result The proposed model outperforms in recommendation accuracy and efficiency.
In 1872 G. Darboux defined a family of curves on surfaces of R^3 which are preserved by the action of the Mobius group and share many properties with geodesics. Here we characterize these curves under the view point of Lorentz geometry and prove some general properties and make them explicit them on simple surfaces, re…
A model predicts user movie preferences based on novelty-seeking traits.
problem Accurately predicting user movie preferences for competitive websites.
method DFNSM model uses demographic, genre, and novelty-seeking data.
result DFNSM outperforms previous models in movie recommendation accuracy.
The Euro (EUR) has been a currency introduced by the European Community on Jan. 01, 1999. This implies eleven countries of the European Union which have been found to meet the five requirements of the Maastricht convergence criteria. In order to test EUR behavior and understand various features, we have extrapolated th…
The paper explores how structured representations influence learning dynamics in neural networks.
problem Understanding the training dynamics of deep neural networks.
method Investigates a family of enriched transformation layers with constrained pathways and adaptive corrections.
result Improved robustness, smoother optimization, and scalable depth behavior are achieved through structured representations.
The paper integrates behavioral finance into asset pricing using subordinated models.
problem Modeling asset returns considering investor behavior and psychological factors.
method Employing subordination to incorporate investor behavior in dynamic asset pricing theory, introducing a mixed Levy subordinated model.
result Option traders overweight the probability of big losses compared to spot traders, showing diminishing sensitivity.
Study f-minimal graphs on manifolds with prescribed boundary behavior.
problem Existence and construction of f-minimal graphs with boundary conditions. method Proving existence and constructing solutions to the asymptotic Dirichlet problem.
result Existence of f-minimal graphs with prescribed boundary behavior and solutions to the asymptotic Dirichlet problem under certain conditions. EigenGame reinterprets PCA as a game to find eigenvectors.
problem Finding principal components efficiently and accurately.
method EigenGame treats PCA as a Nash equilibrium game, using gradient-based updates.
result EigenGame algorithm combines Oja's rule and Gram-Schmidt orthogonalization.
The paper explores how machine learning personalization aligns with humanistic views of the person.
problem Aligning machine learning personalization with humanistic views of the person.
method Explicating the concept of personalization and contrasting it with humanistic views of the person.
result Proposes dimensions for evaluating the degree of personalization of ML personalized scores.
Deep learning classifies animal behavior from wearable accelerometers.
problem Classifying animal behavior from accelerometer data.
method End-to-end deep neural network with IIR and FIR filters.
result Outperforms state-of-the-art algorithms in real-time classification.
Firm foundation theory estimates a security's firm fundamental value based on four determinants: expected growth rate, expected dividend payout, the market interest rate and the degree of risk. In contrast, other views of decision-making in the stock market, using alternatives such as human psychology and behavior, bou…
Study on Monte-Carlo dropout for uncertainty estimation in neural networks.
problem Variability in uncertainty estimation quality through Monte-Carlo dropout.
method Analysis of dropout behavior in neural networks.
result Observation of interesting properties for uncertainty estimation.
A strategy to beat benchmarks by investing in heavily shorted but fundamentally sound securities.
problem Overcoming behavioral biases in investing, particularly the 'rebound effect'.
method Quantitative metrics, historical data, and securities lending modeling.
result The Bounce Basket strategy can outperform market returns during market downturns.
Trading bubbles form when traders adapt to price mismatches.
problem Self-sustained price bubbles driven by adaptive trading behavior.
method Multi-agent model illustrating price bubble formation and statistical properties.
result Price bubbles can be driven by adaptive investment strategies.
Unified model of urban consumer behavior and mobility patterns.
problem Understanding the lifestyles and infrastructure of urban regions.
method Collective matrix factorization for dual view modeling of consumer behavior and mobility.
result Unified model reveals deeper insights into consumer behavior and mobility patterns.
Develops a method to predict system behavior under disruptions.
problem Predicting changes in system behavior due to external perturbations.
method Counterfactual distribution regression for structured inference.
result Generalizes behavior predictions from natural to disrupted states.
Introduces new financial models using subordinated processes.
problem Modeling asset returns with behavioral finance considerations.
method Introduces multiple internally embedded financial time-clocks, subordinated to Brownian motion, with a behavioral subordinator.
result New log-price process with multiple embedded subordinations, requiring estimation of new parameters.
Generalized Hindsight improves RL by reusing data from one task for another.
problem High sample complexity in reinforcement learning due to wasted uninformative data.
method Approximate inverse reinforcement learning to relabel behaviors with better-suited tasks.
result Efficient reuse of samples, reducing sample complexity on multi-task RL tasks.
Method maps gaze fixations to hazards for safer construction.
problem Unrecognized hazards pose safety risks to construction workers.
method Instance segmentation using transfer learning.
result Mapped gaze data improves understanding of hazard recognition.
Around 2008 N. Kawazumi and S. Zhang introduced a new fundamental numerical invariant for compact Riemann surfaces. One way of viewing the Kawazumi-Zhang invariant is as a quotient of two natural hermitian metrics with the same first Chern form on the line bundle of holomorphic differentials. In this paper we determine…
Study quantifies performance gap between tensor and matrix-based approaches in nested matrix-tensor model.
problem Estimating a planted signal in a nested matrix-tensor model.
method Comparing tensor-based and matrix-based approaches for best rank-one approximation of tensor data.
result Derives precise algorithmic threshold for the unfolding approach and shows BBP-type transition behavior.
The numeraire portfolio in a financial market is the unique positive wealth process that makes all other nonnegative wealth processes, when deflated by it, supermartingales. The numeraire portfolio depends on market characteristics, which include: (a) the information flow available to acting agents, given by a filtrati…
New method infers human sensorimotor costs from behavior.
problem Inferring human sensorimotor costs from observed behavior.
method Inverse optimal control with signal-dependent noise.
result Recovering costs and benefits in sensorimotor behavior.
Proposes a novel model for healthcare and SME credit risk prediction.
problem Lack of guidance from global view in sequence representation learning for time series modeling.
method Hierarchical Global View-guided (HGV) sequence representation learning framework with GGE and β-Attn modules. result Competitive prediction performance compared with other known baselines.
New framework shows strategic behavior is actually a form of causal modeling.
problem Designing classifiers that incentivize strategic behavior to improve quality.
method Developed a causal framework to distinguish between gaming and improvement.
result Proved any procedure for designing incentive classifiers must solve a causal inference problem.
Synthesizes computational approaches to understand neural timescales.
problem Varying definitions and measurements of neural timescales across studies.
method Reviews data analysis methods, biophysical models, and machine learning models.
result Complements experimental studies with a holistic view of neural timescales.
Newsroom in online ecosystem is difficult to untangle. With prevalence of social media, interactions between journalists and individuals become visible, but lack of understanding to inner processing of information feedback loop in public sphere leave most journalists baffled. Can we provide an organized view to charact…