Exploiting Universum data in AdaBoost using gradient descent

Recently, Universum data that does not belong to any class of the training data, has been applied for training better classifiers. In this paper, we address a novel boosting algorithm called UAdaBoost that can improve the classification performance of AdaBoost with Universum data. UAdaBoost chooses a function by minimizing the loss for labeled data and Universum data. The cost function is minimized by a greedy, stagewise, functional gradient procedure. Each training stage of UAdaBoost is fast and efficient. The standard AdaBoost weights labeled samples during training iterations while UAdaBoost gives an explicit weighting scheme for Universum samples as well. In addition, this paper describes the practical conditions for the effectiveness of Universum learning. These conditions are based on the analysis of the distribution of ensemble predictions over training samples. Experiments on handwritten digits classification and gender classification problems are presented. As exhibited by our experimental results, the proposed method can obtain superior performances over the standard AdaBoost by selecting proper Universum data. © 2014 Elsevier B.V

Defending Pornography: The Case Against Strategic Essentialism

This chapter offers a critical reading of the discourses employed in the context of the distribution of obscene publications through two recent legal developments in England and Wales. Firstly, in the recent case of R v Peacock, in which a defendant was charged under indictment with six counts of distributing obscene material under Section 2(1) of the Obscene Publications Act 1959 (OPA); and secondly, the recent Audio-Visual Media Services Directive (AVMSD) and its apparent targeting of ‘perverse’ sexual practices. However, rather than focusing on the discourses employed in arguing for regulation, I will to concentrate here on those used to defend pornography against the law. I argue that while in previous cases, classical liberalism tended to be the framing device used to defend pornography on ‘freedom of speech’ grounds, these two recent developments demonstrate that defence advocates and activists alike are utilising a strategic essentialism approach, affixing pornographic representation to sexual orientation or identity. While this approach is certainly strategic, this chapter will reflect on some of the drawbacks of this approach

Fairness in Image Search: A Study of Occupational Stereotyping in Image Retrieval and its Debiasing

Multi-modal search engines have experienced significant growth and widespread use in recent years, making them the second most common internet use. While search engine systems offer a range of services, the image search field has recently become a focal point in the information retrieval community, as the adage goes, "a picture is worth a thousand words". Although popular search engines like Google excel at image search accuracy and agility, there is an ongoing debate over whether their search results can be biased in terms of gender, language, demographics, socio-cultural aspects, and stereotypes. This potential for bias can have a significant impact on individuals' perceptions and influence their perspectives. In this paper, we present our study on bias and fairness in web search, with a focus on keyword-based image search. We first discuss several kinds of biases that exist in search systems and why it is important to mitigate them. We narrow down our study to assessing and mitigating occupational stereotypes in image search, which is a prevalent fairness issue in image retrieval. For the assessment of stereotypes, we take gender as an indicator. We explore various open-source and proprietary APIs for gender identification from images. With these, we examine the extent of gender bias in top-tanked image search results obtained for several occupational keywords. To mitigate the bias, we then propose a fairness-aware re-ranking algorithm that optimizes (a) relevance of the search result with the keyword and (b) fairness w.r.t genders identified. We experiment on 100 top-ranked images obtained for 10 occupational keywords and consider random re-ranking and re-ranking based on relevance as baselines. Our experimental results show that the fairness-aware re-ranking algorithm produces rankings with better fairness scores and competitive relevance scores than the baselines.Comment: 20 Pages, Work uses Proprietary Search Systems from the year 202

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Recent text-to-image generative models can generate high-fidelity images from text inputs, but the quality of these generated images cannot be accurately evaluated by existing evaluation metrics. To address this issue, we introduce Human Preference Dataset v2 (HPD v2), a large-scale dataset that captures human preferences on images from a wide range of sources. HPD v2 comprises 798,090 human preference choices on 433,760 pairs of images, making it the largest dataset of its kind. The text prompts and images are deliberately collected to eliminate potential bias, which is a common issue in previous datasets. By fine-tuning CLIP on HPD v2, we obtain Human Preference Score v2 (HPS v2), a scoring model that can more accurately predict human preferences on generated images. Our experiments demonstrate that HPS v2 generalizes better than previous metrics across various image distributions and is responsive to algorithmic improvements of text-to-image generative models, making it a preferable evaluation metric for these models. We also investigate the design of the evaluation prompts for text-to-image generative models, to make the evaluation stable, fair and easy-to-use. Finally, we establish a benchmark for text-to-image generative models using HPS v2, which includes a set of recent text-to-image models from the academic, community and industry. The code and dataset is available at https://github.com/tgxs002/HPSv2 .Comment: Revisio

The discursive construction of hegemonic and pariah femininities in the spoken accounts of a group of Japanese women

This thesis investigates the discursive construction of culturally idealised (‘hegemonic’) and alternative (‘pariah’) femininities in the spoken accounts of a group of Japanese women. Semi-structured individual and group interviews were conducted with a sample of women and the data was analysed using a Critical Discursive Psychology (CDP) approach. This study makes a contribution to both gender theory and critical discursive psychology. It contributes to gender theory by empirically investigating the theoretical constructs of ‘hegemonic’ and ‘pariah’ femininities. The results of this study indicate that a full-time homemaker is a culturally dominant image of hegemonic femininity. In contrast, working professional women challenge and potentially subvert the homemaker image and thus can be seen as ‘pariah’ femininities. Second, this study fills a gap in existing research by attempting to relate concepts from discursive psychology to characteristic discursive features. These relationships suggest that critical discursive psychologists can make claims about the workings of gender hegemony assisted by identifying participants’ use of characteristic discursive features. Inquiries such as this one contribute to closing the gap between critical discursive psychology and discourse analysis and the development of a more robust and synthetic form of discourse analysis

Logical omniscience at the laboratory

This paper investigates the ability of individuals to make complex chains of reasoning, similar to those underlying the logic of iterated deletion of dominated strategies. Controlling for other-regarding preferences and beliefs about the rationality of others, we show, in the laboratory, that the ability of individuals to perform complex chains of iterative reasoning is better than previously thought. We conclude this from comparing our results with those from studies that use the same game without controlling for confounding factors. Subjects were able to perform about two to three iterations of reasoning on average as measured by our version of the Red-Hat Puzzle

African-American women\u27s reception influence and utility of television content: an exploratory qualitative analysis

This qualitative study featured 33 in-depth interviews of college-aged, African-American women and offers baseline exploratory data about how a majority cultural artifact like televised depictions become utilized in the everyday lives of an underrepresented group in media studies. This research represents one of a few studies to explore how black females decode and utilize TV content, and offers a new theoretical framework to explain informants\u27 decoded receptions, influence and utility of television. An inductive analysis of interview narratives found that viewers use TV content like a looking-glass to understand how they are seen by others and where they fit in the larger social arena. Television\u27s normative cultural reflections are received, decoded, absorbed and self-applied to improve or enhance the social acceptability of black, female interpretive group members. The incidental lessons learned from the television mirror suggest that changing or reinventing oneself based on information gathered from TV content enhances viewers\u27 satisfaction with themselves. Through TV transcripts black female informants in this study learn how they might improve their personal images to assimilate better into the social and professional circles of Caucasian-American lifestyles. Television\u27s ubiquitous nature warrants a closer look at its influence and utility on TV audiences. This study posits that unwitting social and personal reasons promote the heavy television viewing behavior of African-American interpretive group members