arXiv research

Characterizes graphs with leveled embeddings and introduces new graph invariants.

This paper analyzes user-level local differential privacy in distributed systems.

Music FaderNets learns high-level musical qualities from low-level attributes.

Deep reinforcement learning (RL) has shown impressive results in a variety of domains, learning directly from high-dimensional sensory streams. However, when neural networks are trained in a fixed environment, such as a single level in a video game, they will usually overfit and fail to generalize to new levels. When R…

The paper discovers and evaluates support and resistance levels in financial time series.

Minimal graph level sets are concave if boundary is concave.

BILBO optimizes bilevel problems without repeated lower-level optimizations.

We applied Generative Adversarial Networks (GANs) to learn a model of DOOM levels from human-designed content. Initially, we analysed the levels and extracted several topological features. Then, for each level, we extracted a set of images identifying the occupied area, the height map, the walls, and the position of ga…

The paper tackles multi-level fairness in algorithmic systems, addressing bias at both individual and structural levels.

This paper reports the performances of shallow word-level convolutional neural networks (CNN), our earlier work (2015), on the eight datasets with relatively large training data that were used for testing the very deep character-level CNN in Conneau et al. (2016). Our findings are as follows. The shallow word-level CNN…

FRESH combines patient-level and aggregate-level data for better clinical decision making.

New framework tackles bi-level optimization without LLS condition.

This paper improves level generation using VAEs for coherent, logically following segments.

GMVAEs cluster and generate game levels without labels.

TOAD-GAN generates coherent game levels from a single example.

\textit{Multiple Instance Learning} (MIL) is concerned with learning from bags of instances, where only bag labels are given and instance labels are unknown. Existent approaches in this field were mainly designed for the bag-level label prediction (predict labels for bags) but not the instance-level (predict labels for…

Paper explores generalization of AID-based bi-level optimization methods.

The paper calculates dimensions of higher Landau levels on compact manifolds.

Study compares hypergraph and graph-level models for higher-order relational learning.

For leveled spatial graphs, we find a surface embedding that allows cellular embedding.

Researchers infer firm-level supply chain networks from sector-level data to assess systemic risk.

This paper shows how path spaces on two-level manifolds can be Hilbert manifold structures.

Bi-GNN models drug interactions using a bi-level graph approach.

We present a novel solution to the problem of simulation-to-real transfer, which builds on recent advances in robot skill decomposition. Rather than focusing on minimizing the simulation-reality gap, we learn a set of diverse policies that are parameterized in a way that makes them easily reusable. This diversity and p…

Same cohomology for curves with levels, proving stable range.

Develops a method to ensure accurate quantile forecasts across multiple levels.

Trajectory-level supervision allows efficient offline reinforcement learning.

A new method for solving complex sequential decision-making problems by decomposing them into multiple levels.

Any knot $K$ in genus-$1$ $1$-bridge position can be moved by isotopy to lie in a union of $n$ parallel tori tubed by $n-1$ tubes so that $K$ intersects each tube in two spanning arcs, which we call a leveling of the position. The minimal $n$ for which this is possible is an invariant of the position, called the level …

Study shows how $\operatorname{SL}_2$ Hitchin connection at level four behaves.

Quantum representations of mapping class groups are locally rigid at prime levels.

Novel method for bilevel optimization with convex lower-level problem.

New algorithm optimizes adaptive return level for Markowitz portfolios.

RocketStack integrates predictions from multiple base learners using a recursive stacking architecture up to ten levels.

Forecasts of multivariate probability distributions are required for a variety of applications. Scoring rules enable the evaluation of forecast accuracy, and comparison between forecasting methods. We propose a theoretical framework for scoring rules for multivariate distributions, which encompasses the existing quadra…

End-to-end automatic speech recognition (ASR) commonly transcribes audio signals into sequences of characters while its performance is evaluated by measuring the word-error rate (WER). This suggests that predicting sequences of words directly may be helpful instead. However, training with word-level supervision can be …

New algorithm stabilizes bi-level hyperparameter optimization.

We study Veech groups of covering surfaces of primitive translation surfaces. Therefore we define congruence subgroups in Veech groups of primitive translation surfaces using their action on the homology with entries in $\mathbb{Z}/a\mathbb{Z}$. We introduce a congruence level definition and a property of a primitive t…

Playing repeated matrix games (RMG) while maximizing the cumulative returns is a basic method to evaluate multi-agent learning (MAL) algorithms. Previous work has shown that $UCB$, $M3$, $S$ or $Exp3$ algorithms have good behaviours on average in RMG. Besides, hedging algorithms have been shown to be effective on predi…

Study on transnormal functions and their level sets on Finsler manifolds.

The paper finds optimal levels for traders in mean-reverting markets.

Study approximates unknown function levels with queries.

As mobile devices become more and more popular, mobile gaming has emerged as a promising market with billion-dollar revenues. A variety of mobile game platforms and services have been developed around the world. A critical challenge for these platforms and services is to understand the churn behavior in mobile games, w…

Using a recently developed method of noise level estimation that makes use of properties of the coarse grained-entropy we have analyzed the noise level for the Dow Jones index and a few stocks from the New York Stock Exchange. We have found that the noise level ranges from 40 to 80 percent of the signal variance. The c…

Study on Chern-Simons theory at generic levels, revealing universal resurgent structure.

We propose and analyze a constrained level-set method for semi-automatic image segmentation. Our level-set model with constraints on the level-set function enables us to specify which parts of the image lie inside respectively outside the segmented objects. Such a-priori information can be expressed in terms of upper a…

Investigates a new measure PELVE_n for risk assessment.

Policy certifies inventory levels meeting service requirements.