Do you want to publish a course? Click here

Modern deep learning models for natural language processing rely heavily on large amounts of annotated texts. However, obtaining such texts may be difficult when they contain personal or confidential information, for example, in health or legal domai ns. In this work, we propose a method of de-identifying free-form text documents by carefully redacting sensitive data in them. We show that our method preserves data utility for text classification, sequence labeling and question answering tasks.
Neural language models are known to have a high capacity for memorization of training samples. This may have serious privacy im- plications when training models on user content such as email correspondence. Differential privacy (DP), a popular choice to train models with privacy guarantees, comes with significant costs in terms of utility degradation and disparate impact on subgroups of users. In this work, we introduce two privacy-preserving regularization methods for training language models that enable joint optimization of utility and privacy through (1) the use of a discriminator and (2) the inclusion of a novel triplet-loss term. We compare our methods with DP through extensive evaluation. We show the advantages of our regularizers with favorable utility-privacy trade-off, faster training with the ability to tap into existing optimization approaches, and ensuring uniform treatment of under-represented subgroups.
The robustness and security of natural language processing (NLP) models are significantly important in real-world applications. In the context of text classification tasks, adversarial examples can be designed by substituting words with synonyms unde r certain semantic and syntactic constraints, such that a well-trained model will give a wrong prediction. Therefore, it is crucial to develop techniques to provide a rigorous and provable robustness guarantee against such attacks. In this paper, we propose WordDP to achieve certified robustness against word substitution at- tacks in text classification via differential privacy (DP). We establish the connection between DP and adversarial robustness for the first time in the text domain and propose a conceptual exponential mechanism-based algorithm to formally achieve the robustness. We further present a practical simulated exponential mechanism that has efficient inference with certified robustness. We not only provide a rigorous analytic derivation of the certified condition but also experimentally compare the utility of WordDP with existing defense algorithms. The results show that WordDP achieves higher accuracy and more than 30X efficiency improvement over the state-of-the-art certified robustness mechanism in typical text classification tasks.
Approved a Syrian legislator confidentiality of postal correspondence and telecommunications protect the right constitutional and legal for a person, expresses hereby expressly intention to protect his privacy and his secrets expressing his though ts and opinions, freedom of thinking, communication and exchange of information, but this does not mean that the freedom of the individual in this secret absolute, but are given by some of the restrictions that allow eavesdropping and compromised in order to achieve justice and the interests of society according to the decision of the Syrian legislature in the Code of Criminal Procedure, as Syrian legislator intervened to devote their protection sometimes in the face of ordinary people, or in the face of tempted to disclosure of public officials at other times, but Syrian legislator omitted to protect the means to contact an updated e-mail correspondence, which is exposed through it for many attacks, which require effective protection avoiding the legislative vacuum.
The setting in novels has captured the novelists' attention in the contemporary literary world. It was considered the link between elements of the novel. It is، after all، the setting of the events، the substantial scope in which characters move and where all conflicts take place. Thus، the setting، with its different types، has preoccupied modern studies which examined the relation between the setting and the narrative elements، especially the character. Studies have preserved to reflect the relation between setting and character and the effect this relation has on forming the setting and giving it specific characteristics depending upon the case and the reality of the Palestinian movement. This relation between setting and character has acquired much importance due to the mutual relation between the two، to the extent that setting، in some novels، has become a basis for the events، a purpose for forming characters، and a conformation for their identity and existence. This research sheds light on setting in SaharKhalife's novels، its role in personifying the Palestinian reality، and studying its importance in the life of the Palestinian character، in addition to showing the role of description in projecting its indicative features and dimensions.
هناك محاولة في هذه الدراسة لمعرفة مدى تأثير القيم و المبادئ الاجتماعية المتوارثة فـي عناصر التصميم في العمارة السكنية لمدينة دمشق من خلال اختيار نماذج مختلفة لمسـاكن تطورت في فترات متعاقبة، من التقليدية إلى المعاصرة، فقد تم رصـد عناصـر التصـميم ال معماري و رصد التغييرات و التعديلات التي تمت عليها. الحسينية دراسة افتقرت إلى الحـد الأدنى من الوعي لمفهوم الخصوصية و الثقافة الاجتماعية السائدة في المجتمع مما أدى إلى تعديلات مرهقة مادياً، و إلى هدر كبير لمواد البناء نتيجة الهدم و إعـادة البنـاء مـن قبـل المستخدمين، و ظهرت مشكلة التضارب بينهم و بين أفكار المعماري، و ذلـك بهـدف إعـادة تحقيق التوازن بين البيئة المبنية و ثقافة الناس و تقاليدهم و ذلك ما انعكـس بشـكل مـادي واضح.
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا