Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userThe H-index can be easily manipulated
246
0
0.0
(
0
)
Added by
Krzysztof R. Apt
Publication date
2013
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
We prove two complexity results about the H-index concerned with the Google scholar merge operation on ones scientific articles. The results show that, although it is hard to merge ones articles in an optimal way, it is easy to merge them in such a way that ones H-index increases. This suggests the need for an alternative scientific performance measure that is resistant to this type of manipulation.
rate research
Read More
Counterfactual explanations are emerging as an attractive option for providing recourse to individuals adversely impacted by algorithmic decisions. As they are deployed in critical applications (e.g. law enforcement, financial lending), it becomes important to ensure that we clearly understand the vulnerabilities of these methods and find ways to address them. However, there is little understanding of the vulnerabilities and shortcomings of counterfactual explanations. In this work, we introduce the first framework that describes the vulnerabilities of counterfactual explanations and shows how they can be manipulated. More specifically, we show counterfactual explanations may converge to drastically different counterfactuals under a small perturbation indicating they are not robust. Leveraging this insight, we introduce a novel objective to train seemingly fair models where counterfactual explanations find much lower cost recourse under a slight perturbation. We describe how these models can unfairly provide low-cost recourse for specific subgroups in the data while appearing fair to auditors. We perform experiments on loan and violent crime prediction data sets where certain subgroups achieve up to 20x lower cost recourse under the perturbation. These results raise concerns regarding the dependability of current counterfactual explanation techniques, which we hope will inspire investigations in robust counterfactual explanations.
As machine learning models are increasingly used in critical decision-making settings (e.g., healthcare, finance), there has been a growing emphasis on developing methods to explain model predictions. Such textit{explanations} are used to understand and establish trust in models and are vital components in machine learning pipelines. Though explanations are a critical piece in these systems, there is little understanding about how they are vulnerable to manipulation by adversaries. In this paper, we discuss how two broad classes of explanations are vulnerable to manipulation. We demonstrate how adversaries can design biased models that manipulate model agnostic feature attribution methods (e.g., LIME & SHAP) and counterfactual explanations that hill-climb during the counterfactual search (e.g., Wachters Algorithm & DiCE) into textit{concealing} the models biases. These vulnerabilities allow an adversary to deploy a biased model, yet explanations will not reveal this bias, thereby deceiving stakeholders into trusting the model. We evaluate the manipulations on real world data sets, including COMPAS and Communities & Crime, and find explanations can be manipulated in practice.
Using the QCD sum rule approach, we show that the flavor-nonsinglet $H$ dibaryon states with J$^{pi} = 1^+$, J$^{pi} = 0^+$, I=1 (27plet) are nearly degenerate with the J$^{pi} = 0^+$, I=0 singlet $H_0$ dibaryon, which has been predicted to be stable against strong decay, but has not been observed. Our calculation, which does not require an instanton correction, suggests that the $H_0$ is slightly heavier than these flavor-nonsinglet $H$s over a wide range of the parameter space. If the singlet $H_0$ mass lies above the $Lambda Lambda$ threshold (2231~MeV), then the strong interaction breakup to $Lambda Lambda$ would produce a very broad resonance in the $Lambda Lambda$ invariant mass spectrum which would be very difficult to observe. On the other hand, if these flavor-nonsinglet J=0 and 1 $H$ dibaryons are also above the $Lambda Lambda$ threshold, but below the $Xi^0n$ breakup threshold (2254 MeV), then because the direct, strong interaction decay to the $Lambda Lambda$ channel is forbidden, these flavor-nonsinglet states might be more amenable to experimental observation. The present results allow a possible reconciliation between the reported observation of $Lambda Lambda$ hypernuclei, which argue against a stable $H_0$, and the possible existence of $H$ dibaryons in general.
On many social networking web sites such as Facebook and Twitter, resharing or reposting functionality allows users to share others content with their own friends or followers. As content is reshared from user to user, large cascades of reshares can form. While a growing body of research has focused on analyzing and characterizing such cascades, a recent, parallel line of work has argued that the future trajectory of a cascade may be inherently unpredictable. In this work, we develop a framework for addressing cascade prediction problems. On a large sample of photo reshare cascades on Facebook, we find strong performance in predicting whether a cascade will continue to grow in the future. We find that the relative growth of a cascade becomes more predictable as we observe more of its reshares, that temporal and structural features are key predictors of cascade size, and that initially, breadth, rather than depth in a cascade is a better indicator of larger cascades. This prediction performance is robust in the sense that multiple distinct classes of features all achieve similar performance. We also discover that temporal features are predictive of a cascades eventual shape. Observing independent cascades of the same content, we find that while these cascades differ greatly in size, we are still able to predict which ends up the largest.
General Relativity has had tremendous successes on both theoretical and experimental fronts for over a century by now. However, the theory contents are far from being exhausted. Only very recently, with gravitational wave detection from colliding black holes, have we started probing gravity behavior in the strongly non-linear regime. Even today, black hole studies keep revealing more and more paradoxes and bizarre results. In this paper, inspired by David Hilberts startling observation, we show that, contrary to the conventional wisdom, a freely falling test particle feels gravitational repulsion by a black hole as seen by an asymptotic observer. We dig deeper into this relativistic gravity surprising behavior and offer some explanations.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
