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  1. Book ; Online: Sequential Nature of Recommender Systems Disrupts the Evaluation Process

    Shirali, Ali

    2022  

    Abstract: Datasets are often generated in a sequential manner, where the previous samples and intermediate decisions or interventions affect subsequent samples. This is especially prominent in cases where there are significant human-AI interactions, such as in ... ...

    Abstract Datasets are often generated in a sequential manner, where the previous samples and intermediate decisions or interventions affect subsequent samples. This is especially prominent in cases where there are significant human-AI interactions, such as in recommender systems. To characterize the importance of this relationship across samples, we propose to use adversarial attacks on popular evaluation processes. We present sequence-aware boosting attacks and provide a lower bound on the amount of extra information that can be exploited from a confidential test set solely based on the order of the observed data. We use real and synthetic data to test our methods and show that the evaluation process on the MovieLense-100k dataset can be affected by $\sim1\%$ which is important when considering the close competition. Codes are publicly available.

    Comment: To Appear in Third International Workshop on Algorithmic Bias in Search and Recommendation (Bias 2022)
    Keywords Computer Science - Information Retrieval ; Computer Science - Artificial Intelligence
    Subject code 006
    Publishing date 2022-05-26
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Book ; Online: What Makes ImageNet Look Unlike LAION

    Shirali, Ali / Hardt, Moritz

    2023  

    Abstract: ImageNet was famously created from Flickr image search results. What if we recreated ImageNet instead by searching the massive LAION dataset based on image captions alone? In this work, we carry out this counterfactual investigation. We find that the ... ...

    Abstract ImageNet was famously created from Flickr image search results. What if we recreated ImageNet instead by searching the massive LAION dataset based on image captions alone? In this work, we carry out this counterfactual investigation. We find that the resulting ImageNet recreation, which we call LAIONet, looks distinctly unlike the original. Specifically, the intra-class similarity of images in the original ImageNet is dramatically higher than it is for LAIONet. Consequently, models trained on ImageNet perform significantly worse on LAIONet. We propose a rigorous explanation for the discrepancy in terms of a subtle, yet important, difference in two plausible causal data-generating processes for the respective datasets, that we support with systematic experimentation. In a nutshell, searching based on an image caption alone creates an information bottleneck that mitigates the selection bias otherwise present in image-based filtering. Our explanation formalizes a long-held intuition in the community that ImageNet images are stereotypical, unnatural, and overly simple representations of the class category. At the same time, it provides a simple and actionable takeaway for future dataset creation efforts.
    Keywords Computer Science - Machine Learning ; Computer Science - Computer Vision and Pattern Recognition
    Subject code 006
    Publishing date 2023-06-27
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Book ; Online: Pruning the Way to Reliable Policies

    Shirali, Ali / Schubert, Alexander / Alaa, Ahmed

    A Multi-Objective Deep Q-Learning Approach to Critical Care

    2023  

    Abstract: Most medical treatment decisions are sequential in nature. Hence, there is substantial hope that reinforcement learning may make it possible to formulate precise data-driven treatment plans. However, a key challenge for most applications in this field is ...

    Abstract Most medical treatment decisions are sequential in nature. Hence, there is substantial hope that reinforcement learning may make it possible to formulate precise data-driven treatment plans. However, a key challenge for most applications in this field is the sparse nature of primarily mortality-based reward functions, leading to decreased stability of offline estimates. In this work, we introduce a deep Q-learning approach able to obtain more reliable critical care policies. This method integrates relevant but noisy intermediate biomarker signals into the reward specification, without compromising the optimization of the main outcome of interest (e.g. patient survival). We achieve this by first pruning the action set based on all available rewards, and second training a final model based on the sparse main reward but with a restricted action set. By disentangling accurate and approximated rewards through action pruning, potential distortions of the main objective are minimized, all while enabling the extraction of valuable information from intermediate signals that can guide the learning process. We evaluate our method in both off-policy and offline settings using simulated environments and real health records of patients in intensive care units. Our empirical results indicate that pruning significantly reduces the size of the action space while staying mostly consistent with the actions taken by physicians, outperforming the current state-of-the-art offline reinforcement learning method conservative Q-learning. Our work is a step towards developing reliable policies by effectively harnessing the wealth of available information in data-intensive critical care environments.

    Comment: IEEE copyright notice added
    Keywords Computer Science - Machine Learning ; Computer Science - Artificial Intelligence
    Subject code 006
    Publishing date 2023-06-13
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Using distance on the Riemannian manifold to compare representations in brain and in models.

    Shahbazi, Mahdiyar / Shirali, Ali / Aghajan, Hamid / Nili, Hamed

    NeuroImage

    2021  Volume 239, Page(s) 118271

    Abstract: Representational similarity analysis (RSA) summarizes activity patterns for a set of experimental conditions into a matrix composed of pairwise comparisons between activity patterns. Two examples of such matrices are the condition-by-condition inner ... ...

    Abstract Representational similarity analysis (RSA) summarizes activity patterns for a set of experimental conditions into a matrix composed of pairwise comparisons between activity patterns. Two examples of such matrices are the condition-by-condition inner product and correlation matrix. These representational matrices reside on the manifold of positive semidefinite matrices, called the Riemannian manifold. We hypothesize that representational similarities would be more accurately quantified by considering the underlying manifold of the representational matrices. Thus, we introduce the distance on the Riemannian manifold as a metric for comparing representations. Analyzing simulated and real fMRI data and considering a wide range of metrics, we show that the Riemannian distance is least susceptible to sampling bias, results in larger intra-subject reliability, and affords searchlight mapping with high sensitivity and specificity. Furthermore, we show that the Riemannian distance can be used for measuring multi-dimensional connectivity. This measure captures both univariate and multivariate connectivity and is also more sensitive to nonlinear regional interactions compared to the state-of-the-art measures. Applying our proposed metric to neural network representations of natural images, we demonstrate that it also possesses outstanding performance in quantifying similarity in models. Taken together, our results lend credence to the proposition that RSA should consider the manifold of the representational matrices to summarize response patterns in the brain and in models.
    MeSH term(s) Algorithms ; Brain Mapping ; Computer Simulation ; Humans ; Image Processing, Computer-Assisted/methods ; Models, Neurological ; Multivariate Analysis ; Neural Networks, Computer ; Neuroimaging/methods ; Nonlinear Dynamics ; Pattern Recognition, Automated/methods
    Language English
    Publishing date 2021-06-19
    Publishing country United States
    Document type Comparative Study ; Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1147767-2
    ISSN 1095-9572 ; 1053-8119
    ISSN (online) 1095-9572
    ISSN 1053-8119
    DOI 10.1016/j.neuroimage.2021.118271
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Book ; Online: A Theory of Dynamic Benchmarks

    Shirali, Ali / Abebe, Rediet / Hardt, Moritz

    2022  

    Abstract: Dynamic benchmarks interweave model fitting and data collection in an attempt to mitigate the limitations of static benchmarks. In contrast to an extensive theoretical and empirical study of the static setting, the dynamic counterpart lags behind due to ... ...

    Abstract Dynamic benchmarks interweave model fitting and data collection in an attempt to mitigate the limitations of static benchmarks. In contrast to an extensive theoretical and empirical study of the static setting, the dynamic counterpart lags behind due to limited empirical studies and no apparent theoretical foundation to date. Responding to this deficit, we initiate a theoretical study of dynamic benchmarking. We examine two realizations, one capturing current practice and the other modeling more complex settings. In the first model, where data collection and model fitting alternate sequentially, we prove that model performance improves initially but can stall after only three rounds. Label noise arising from, for instance, annotator disagreement leads to even stronger negative results. Our second model generalizes the first to the case where data collection and model fitting have a hierarchical dependency structure. We show that this design guarantees strictly more progress than the first, albeit at a significant increase in complexity. We support our theoretical analysis by simulating dynamic benchmarks on two popular datasets. These results illuminate the benefits and practical limitations of dynamic benchmarking, providing both a theoretical foundation and a causal explanation for observed bottlenecks in empirical work.

    Comment: ICLR 2023 Version
    Keywords Computer Science - Machine Learning ; Statistics - Machine Learning
    Subject code 005
    Publishing date 2022-10-06
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Book ; Online: On the Effect of Triadic Closure on Network Segregation

    Abebe, Rediet / Immorlica, Nicole / Kleinberg, Jon / Lucier, Brendan / Shirali, Ali

    2022  

    Abstract: The tendency for individuals to form social ties with others who are similar to themselves, known as homophily, is one of the most robust sociological principles. Since this phenomenon can lead to patterns of interactions that segregate people along ... ...

    Abstract The tendency for individuals to form social ties with others who are similar to themselves, known as homophily, is one of the most robust sociological principles. Since this phenomenon can lead to patterns of interactions that segregate people along different demographic dimensions, it can also lead to inequalities in access to information, resources, and opportunities. As we consider potential interventions that might alleviate the effects of segregation, we face the challenge that homophily constitutes a pervasive and organic force that is difficult to push back against. Designing effective interventions can therefore benefit from identifying counterbalancing social processes that might be harnessed to work in opposition to segregation. In this work, we show that triadic closure -- another common phenomenon that posits that individuals with a mutual connection are more likely to be connected to one another -- can be one such process. In doing so, we challenge a long-held belief that triadic closure and homophily work in tandem. By analyzing several fundamental network models using popular integration measures, we demonstrate the desegregating potential of triadic closure. We further empirically investigate this effect on real-world dynamic networks, surfacing observations that mirror our theoretical findings. We leverage these insights to discuss simple interventions that can help reduce segregation in settings that exhibit an interplay between triadic closure and homophily. We conclude with a discussion on qualitative implications for the design of interventions in settings where individuals arrive in an online fashion, and the designer can influence the initial set of connections.

    Comment: To Appear in Proceedings of the 23rd ACM Conference on Economics and Computation (EC'22)
    Keywords Computer Science - Social and Information Networks ; Economics - Theoretical Economics
    Publishing date 2022-05-26
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article: Molar pregnancy presents as tubal ectopic pregnancy.

    Tanha, Fatemeh Davari / ShirAli, Elham / Rahmanpour, Haleh / Haghollahi, Fediey

    International journal of fertility & sterility

    2011  Volume 4, Issue 4, Page(s) 184–186

    Abstract: Hydatidiform moles are abnormal gestations characterized by the presence of hydropic changes affecting some or all of the placental villi. Hydatidiform moles arise as a result of the fertilization of an abnormal ovum. In this report, the patient was a 29 ...

    Abstract Hydatidiform moles are abnormal gestations characterized by the presence of hydropic changes affecting some or all of the placental villi. Hydatidiform moles arise as a result of the fertilization of an abnormal ovum. In this report, the patient was a 29 year old Asian woman who had induction of ovulation with letrozol. Since the majority of molar gestations arise within the uterine cavity thus the occurrence of a hydatidiform mole within ectopic gestational tissue is rare. It is important to differentiate a hydatidiform mole from a conventional ectopic pregnancy, particularly in infertile women who have a history of ovulation induction.
    Language English
    Publishing date 2011-02-20
    Publishing country Iran
    Document type Journal Article
    ZDB-ID 2570865-X
    ISSN 2008-0778 ; 2008-076X
    ISSN (online) 2008-0778
    ISSN 2008-076X
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Molar Pregnancy Presents as Tubal Ectopic Pregnancy

    Fatemeh Davari Tanha / Elham ShirAli / Haleh Rahmanpour / Fediey Haghollahi

    International Journal of Fertility and Sterility, Vol 4, Iss 4, Pp 184-

    2011  Volume 186

    Abstract: Hydatidiform moles are abnormal gestations characterized by the presence of hydropic changesaffecting some or all of the placental villi. Hydatidiform moles arise as a result of the fertilizationof an abnormal ovum. In this report, the patient was a 29 ... ...

    Abstract Hydatidiform moles are abnormal gestations characterized by the presence of hydropic changesaffecting some or all of the placental villi. Hydatidiform moles arise as a result of the fertilizationof an abnormal ovum. In this report, the patient was a 29 year old Asian woman who had inductionof ovulation with letrozol. Since the majority of molar gestations arise within the uterine cavitythus the occurrence of a hydatidiform mole within ectopic gestational tissue is rare. It is importantto differentiate a hydatidiform mole from a conventional ectopic pregnancy, particularly in infertilewomen who have a history of ovulation induction.
    Keywords Hydatidiform Mole ; Ectopic Pregnancy ; Choriocarcinoma ; Medicine (General) ; R5-920
    Language English
    Publishing date 2011-01-01T00:00:00Z
    Publisher Royan Institute
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Molar Pregnancy Presents as Tubal Ectopic Pregnancy

    Fatemeh Davari Tanha / Elham ShirAli / Haleh Rahmanpour / Fediey Haghollahi

    International Journal of Fertility and Sterility, Vol 4, Iss 4, Pp 184-

    2011  Volume 186

    Abstract: Hydatidiform moles are abnormal gestations characterized by the presence of hydropic changes affecting some or all of the placental villi. Hydatidiform moles arise as a result of the fertilization of an abnormal ovum. In this report, the patient was a 29 ...

    Abstract Hydatidiform moles are abnormal gestations characterized by the presence of hydropic changes affecting some or all of the placental villi. Hydatidiform moles arise as a result of the fertilization of an abnormal ovum. In this report, the patient was a 29 year old Asian woman who had induction of ovulation with letrozol. Since the majority of molar gestations arise within the uterine cavity thus the occurrence of a hydatidiform mole within ectopic gestational tissue is rare. It is important to differentiate a hydatidiform mole from a conventional ectopic pregnancy, particularly in infertile women who have a history of ovulation induction.
    Keywords hydatidiform mole ; ectopic pregnancy ; choriocarcinoma ; Medicine (General) ; R5-920
    Language English
    Publishing date 2011-01-01T00:00:00Z
    Publisher Royan Institute (ACECR), Tehran
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: Molar Pregnancy Presents as Tubal Ectopic Pregnancy

    Fatemeh Davari Tanha / Elham ShirAli / Haleh Rahmanpour / Fediey Haghollahi

    International Journal of Fertility and Sterility, Vol 4, Iss 4, Pp 184-

    2011  Volume 186

    Abstract: Hydatidiform moles are abnormal gestations characterized by the presence of hydropic changes affecting some or all of the placental villi. Hydatidiform moles arise as a result of the fertilization of an abnormal ovum. In this report, the patient was a 29 ...

    Abstract Hydatidiform moles are abnormal gestations characterized by the presence of hydropic changes affecting some or all of the placental villi. Hydatidiform moles arise as a result of the fertilization of an abnormal ovum. In this report, the patient was a 29 year old Asian woman who had induction of ovulation with letrozol. Since the majority of molar gestations arise within the uterine cavity thus the occurrence of a hydatidiform mole within ectopic gestational tissue is rare. It is important to differentiate a hydatidiform mole from a conventional ectopic pregnancy, particularly in infertile women who have a history of ovulation induction.
    Keywords hydatidiform mole ; ectopic pregnancy ; choriocarcinoma ; Medicine (General) ; R5-920
    Language English
    Publishing date 2011-01-01T00:00:00Z
    Publisher Royan Institute (ACECR), Tehran
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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