arXiv research

A cased-based reasoning method predicts rare events on strategic sites using satellite imagery.

Estimates users' preference for a site over others using engagement data.

Site-specific recombination is an enzymatic process where two sites of precise sequence and orientation along a circle come together, are cleaved, and the ends are recombined. Site-specific recombination on a knotted substrate produces another knot or a two-component link depending on the relative orientation of the si…

Paper tackles robust decision-making from multiple sites with shared structure.

Clinical AI models fail to transfer between sites due to site-specific practices.

A novel machine learning optimization process coined Restrictive Federated Model Selection (RFMS) is proposed under the scenario, for example, when data from healthcare units can not leave the site it is situated on and it is forbidden to carry out training algorithms on remote data sites due to either technical or pri…

A novel framework synthesizes treatment data across sites using optimal transport.

Meta-analysis improves personalized treatment rules across multiple sites.

Tree-based model averaging improves CATE estimation from diverse sites.

A rational knot or link can be put into a standard alternating format which has horizontal and vertical twist sites (double helices). The number and type of these twist sites are determined by terms of next-to-highest $z$-degree in Kauffman's regular isotopy invariant $Λ(a,z)$. In particular, for a knot or link with $c…

The study explores how different Grothendieck topologies and functors between categories preserve locality.

The research reported in this paper identifies the epigenetic biomarker (methylation beta pattern) of breast cancer. Many cancers are triggered by abnormal gene expression levels caused by aberrant methylation of CpG sites in the DNA. In order to develop early diagnostics of cancer-causing methylations and to develop a…

Paper tackles online facility location with user requests and provides a quasi-linear time algorithm.

New framework for robust uncertainty quantification in strategic settings.

New federated method preserves privacy and estimates treatment effects.

Method improves robustness and generalizability of CATE estimation.

A site-specific Gordian distance between two spatial embeddings of an abstract graph is the minimal number of crossing changes from one to another where each crossing change is performed between two previously specified abstract edges of the graph. It is infinite in some cases. We determine the site-specific Gordian di…

Owners of a web-site are often interested in analysis of groups of users of their site. Information on these groups can help optimizing the structure and contents of the site. In this paper we use an approach based on formal concepts for constructing taxonomies of user groups. For decreasing the huge amount of concepts…

Paper proves model structures equal for smooth manifolds and Cartesian spaces.

Paper generalizes strategic classification framework and introduces SVC for PAC-learning.

Study strategic dynamic pricing for buyers with unknown manipulation costs.

Site-specific recombination on supercoiled circular DNA molecules can yield a variety of knots and catenanes. Twist knots are some of the most common conformations of these products and they can act as substrates for further rounds of site-specific recombination. They are also one of the simplest families of knots and …

FONT clusters patients across health systems with privacy and efficiency.

New framework reduces strategic manipulation cost for minority groups in fair classification.

Study compares employers with and without anticipating strategic labor force responses.

Connectivity studies using resting-state functional magnetic resonance imaging are increasingly pooling data acquired at multiple sites. While this may allow investigators to speed up recruitment or increase sample size, multisite studies also potentially introduce systematic biases in connectivity measures across site…

RNA-binding proteins (RBPs) play crucial roles in many biological processes, e.g. gene regulation. Computational identification of RBP binding sites on RNAs are urgently needed. In particular, RBPs bind to RNAs by recognizing sequence motifs. Thus, fast locating those motifs on RNA sequences is crucial and time-efficie…

New algorithm learns optimal policies in strategic MDPs with private types.

Deep neural network (DNN) has demonstrated its success in multiple domains. However, DNN models are inherently vulnerable to adversarial examples, which are generated by adding adversarial perturbations to benign inputs to fool the DNN model to misclassify. In this paper, we present a cross-layer strategic ensemble fra…

Desingularizes singular spaces using sheaves and groupoids.

PLOT uses optimal transport to find neural site handles for causal abstraction.

New findings show strategic interactions can undermine model expressiveness in machine learning.

HBR improves normative modeling of neuroimaging data across multiple sites.

Consequential decision-making typically incentivizes individuals to behave strategically, tailoring their behavior to the specifics of the decision rule. A long line of work has therefore sought to counteract strategic behavior by designing more conservative decision boundaries in an effort to increase robustness to th…

Paper proposes federated offline RL for personalized medicine.

Strategic feature selection in high-stakes domains like healthcare.

Study allocates resources to strategic agents while balancing cost and incentives.

The paper analyzes trading strategies in a competitive market with incomplete information.

Algorithm learns optimal coordination for strategic agents in uncertain settings.

Randomised classifiers outperform deterministic ones in strategic classification.

Study one-shot strategic classification under unknown costs, improving worst-case accuracy.

Consequential decision-making incentivizes individuals to strategically adapt their behavior to the specifics of the decision rule. While a long line of work has viewed strategic adaptation as gaming and attempted to mitigate its effects, recent work has instead sought to design classifiers that incentivize individuals…

We consider a symmetric multi-players zero-sum game with two strategic variables. There are $n$ players, $n\geq 3$. Each player is denoted by $i$. Two strategic variables are $t_i$ and $s_i$, $i\in \{1, \dots, n\}$. They are related by invertible functions. Using the minimax theorem by \cite{sion} we will show that Nas…

Masked LARk prevents cross-site tracking while training models.

We study a strategic version of the multi-armed bandit problem, where each arm is an individual strategic agent and we, the principal, pull one arm each round. When pulled, the arm receives some private reward $v_a$ and can choose an amount $x_a$ to pass on to the principal (keeping $v_a-x_a$ for itself). All non-pulle…

COBRA addresses strategic behavior in online platforms by ensuring truthful reporting without monetary incentives.

Strategic feature manipulation helps learners identify meaningful variables in online regression settings.

The results of a learning process depend on the input data. There are cases in which an adversary can strategically tamper with the input data to affect the outcome of the learning process. While some datasets are difficult to attack, many others are susceptible to manipulation. A resourceful attacker can tamper with l…