Daniel Kifer - RankMe

158 papers A* 37A 9B 1C 1Journal 93Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Composition for Pufferfish Privacy. CoRR Jiamu Bai, Guanlin He, Xin Gu, Daniel Kifer, Kiwan Maeng
2026	J	`jnl`	Fast Private Adaptive Query Answering for Large Data Domains. CoRR Miguel Fuentes, Brett Mullins, Yingtai Xiao, Daniel Kifer, Cameron Musco, Daniel Sheldon
2025	C	`conf`	Bridging Neural and Symbolic Computation: A Learnability Study of RNNs on Counter and Dyck Languages. NeSy Neisarg Dave, Daniel Kifer, C. Lee Giles, Ankur Mali
2025	A*	`conf`	Click Without Compromise: Online Advertising Measurement via Per User Differential Privacy. SP Yingtai Xiao, Jian Du, Shikun Zhang, Wanrong Zhang, Qian Yang, Danfeng Zhang, Daniel Kifer
2025	J	`jnl`	Correlating Cross-Iteration Noise for DP-SGD using Model Curvature. CoRR Xin Gu, Yingtai Xiao, Guanlin He, Jiamu Bai, Daniel Kifer, Kiwan Maeng
2025	A*	`conf`	Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations. ICLR Abdolmehdi Behroozi, Chaopeng Shen, Daniel Kifer
2025	J	`jnl`	Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations. CoRR Abdolmehdi Behroozi, Chaopeng Shen, Daniel Kifer
2025	J	`jnl`	Statistics-Friendly Confidentiality Protection for Establishment Data, with Applications to the QCEW. CoRR Kaitlyn Webb, Prottay Protivash, John Durrell, Daniell Toth, Aleksandra B. Slavkovic, Daniel Kifer
2025	J	`jnl`	StefaLand: An Efficient Geoscience Foundation Model That Improves Dynamic Land-Surface Predictions. CoRR Nicholas Kraabel, Jiangtao Liu, Yuchen Bian, Daniel Kifer, Chaopeng Shen
2025	J	`jnl`	Towards Better Optimization For Listwise Preference in Diffusion Models. CoRR Jiamu Bai, Xin Yu, Meilong Xu, Weitao Lu, Xin Pan, Kiwan Maeng, Daniel Kifer, Jian Wang, Yu Wang
2024	J	`jnl`	Click Without Compromise: Online Advertising Measurement via Per User Differential Privacy. CoRR Yingtai Xiao, Jian Du, Shikun Zhang, Qiang Yan, Danfeng Zhang, Daniel Kifer
2024	A*	`conf`	Efficient and Private Marginal Reconstruction with Local Non-Negativity. NeurIPS Brett Mullins, Miguel Fuentes, Yingtai Xiao, Daniel Kifer, Cameron Musco, Daniel R. Sheldon
2024	J	`jnl`	Efficient and Private Marginal Reconstruction with Local Non-Negativity. CoRR Brett Mullins, Miguel Fuentes, Yingtai Xiao, Daniel Kifer, Cameron Musco, Daniel Sheldon
2024	J	`jnl`	Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism. J. Priv. Confidentiality Arjun Wilkins, Daniel Kifer, Danfeng Zhang, Brian Karrer
2024	J	`jnl`	Geographic Spines in the 2020 Census Disclosure Avoidance System. J. Priv. Confidentiality Ryan Cumings-Menon, Robert Ashmead, Daniel Kifer, Philip Leclerc, Jeffrey Ocker, Michael Ratcliffe, Pavel Zhuravlev, John M. Abowd
2024	—	`conf`	Investigating Symbolic Capabilities of Large Language Models. LNSAI@IJCAI Neisarg Dave, Daniel Kifer, C. Lee Giles, Ankur Mali
2024	J	`jnl`	Investigating Symbolic Capabilities of Large Language Models. CoRR Neisarg Dave, Daniel Kifer, C. Lee Giles, Ankur Mali
2024	A	`conf`	PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise Binarization. WACV Savinay Nagendra, Daniel Kifer
2024	J	`jnl`	Precision, Stability, and Generalization: A Comprehensive Assessment of RNNs learnability capability for Classifying Counter and Dyck Languages. CoRR Neisarg Dave, Daniel Kifer, C. Lee Giles, Ankur Mali
2024	J	`jnl`	Reconstruction Attacks on Aggressive Relaxations of Differential Privacy. J. Priv. Confidentiality Prottay Protivash, John Durrell, Daniel Kifer, Zeyu Ding, Danfeng Zhang
2024	J	`jnl`	SAMIC: Segment Anything with In-Context Spatial Prompt Engineering. CoRR Savinay Nagendra, Kashif Rashid, Chaopeng Shen, Daniel Kifer
2024	J	`jnl`	Stability Analysis of Various Symbolic Rule Extraction Methods from Recurrent Neural Network. CoRR Neisarg Dave, Daniel Kifer, C. Lee Giles, Ankur Mali
2023	J	`jnl`	A Floating-Point Secure Implementation of the Report Noisy Max with Gap Mechanism. CoRR Zeyu Ding, John Durrell, Daniel Kifer, Prottay Protivash, Guanhong Wang, Yuxin Wang, Yingtai Xiao, Danfeng Zhang
2023	J	`jnl`	An In-Depth Examination of Requirements for Disclosure Risk Assessment. CoRR Ron S. Jarmin, John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Nathan Goldschlag, Michael B. Hawes, Sallie Ann Keller, Daniel Kifer, Philip Leclerc, Jerome P. Reiter, Rolando A. Rodríguez, Ian M. Schmutte, Victoria A. Velkoff, Pavel Zhuravlev
2023	A*	`conf`	An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions. NeurIPS Yingtai Xiao, Guanlin He, Danfeng Zhang, Daniel Kifer
2023	J	`jnl`	An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions. CoRR Yingtai Xiao, Guanlin He, Danfeng Zhang, Daniel Kifer
2023	J	`jnl`	Answering Private Linear Queries Adaptively using the Common Mechanism. Proc. VLDB Endow. Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer
2023	A*	`conf`	Backpropagation-Free Deep Learning with Recursive Local Representation Alignment. AAAI Alexander G. Ororbia II, Ankur Mali, Daniel Kifer, C. Lee Giles
2023	J	`jnl`	Differentiable modeling to unify machine learning and physical models and advance Geosciences. CoRR Chaopeng Shen, Alison P. Appling, Pierre Gentine, Toshiyuki Bandai, Hoshin V. Gupta, Alexandre Tartakovsky, Marco Baity-Jesi, Fabrizio Fenicia, Daniel Kifer, Li Li, Xiaofeng Liu, Wei Ren, Yi Zheng, Ciaran J. Harman, Martyn P. Clark, Matthew W. Farthing, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Hylke E. Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Tirthankar Roy, Chonggang Xu, Kathryn Lawson
2023	J	`jnl`	Disclosure Avoidance for the 2020 Census Demographic and Housing Characteristics File. CoRR Ryan Cumings-Menon, Robert Ashmead, Daniel Kifer, Philip Leclerc, Matthew Spence, Pavel Zhuravlev, John M. Abowd
2023	J	`jnl`	Estimating Uncertainty in Landslide Segmentation Models. CoRR Savinay Nagendra, Chaopeng Shen, Daniel Kifer
2023	J	`jnl`	Free gap estimates from the exponential mechanism, sparse vector, noisy max and related algorithms. VLDB J. Zeyu Ding, Yuxin Wang, Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer
2023	J	`jnl`	On the Computational Complexity and Formal Hierarchy of Second Order Recurrent Neural Networks. CoRR Ankur Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
2023	J	`jnl`	On the Tensor Representation and Algebraic Homomorphism of the Neural State Turing Machine. CoRR Ankur Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
2023	J	`jnl`	The 2010 Census Confidentiality Protections Failed, Here's How and Why. CoRR John M. Abowd, Tamara Adams, Robert Ashmead, David Darais, Sourya Dey, Simson L. Garfinkel, Nathan Goldschlag, Daniel Kifer, Philip Leclerc, Ethan Lew, Scott Moore, Rolando A. Rodríguez, Ramy N. Tadros, Lars Vilhuber
2022	J	`jnl`	An Empirical Analysis of Recurrent Learning Algorithms In Neural Lossy Image Compression Systems. CoRR Ankur Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
2022	J	`jnl`	Answering Private Linear Queries Adaptively using the Common Mechanism. CoRR Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer
2022	J	`jnl`	Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census. CoRR Daniel Kifer, John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Philip Leclerc, Ashwin Machanavajjhala, William Sexton, Pavel Zhuravlev
2022	J	`jnl`	Constructing a Large-Scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. Savinay Nagendra, Daniel Kifer, Benjamin Mirus, Te Pei, Kathryn Lawson, Srikanth Banagere Manjunatha, Weixin Li, Hien Nguyen, Tong Qiu, Sarah Tran, Chaopeng Shen
2022	J	`jnl`	Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism. CoRR Brian Karrer, Daniel Kifer, Arjun Wilkins, Danfeng Zhang
2022	J	`jnl`	Geographic Spines in the 2020 Census Disclosure Avoidance System TopDown Algorithm. CoRR John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Daniel Kifer, Philip Leclerc, Jeffrey Ocker, Michael Ratcliffe, Pavel Zhuravlev
2022	A*	`conf`	Lifelong Neural Predictive Coding: Learning Cumulatively Online without Forgetting. NeurIPS Alexander Ororbia, Ankur Mali, C. Lee Giles, Daniel Kifer
2022	B	`conf`	Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder. DCC Ankur Mali, Alexander G. Ororbia II, Daniel Kifer, C. Lee Giles
2022	J	`jnl`	Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder. CoRR Ankur Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
2022	J	`jnl`	Reconstruction Attacks on Aggressive Relaxations of Differential Privacy. CoRR Prottay Protivash, John Durrell, Zeyu Ding, Danfeng Zhang, Daniel Kifer
2022	J	`jnl`	The 2020 Census Disclosure Avoidance System TopDown Algorithm. CoRR John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson L. Garfinkel, Micah Heineck, Christine Heiss, Robert Johns, Daniel Kifer, Philip Leclerc, Ashwin Machanavajjhala, Brett Moran, William Sexton, Matthew Spence, Pavel Zhuravlev
2022	J	`jnl`	ThreshNet: Segmentation Refinement Inspired by Region-Specific Thresholding. CoRR Savinay Nagendra, Chaopeng Shen, Daniel Kifer
2021	A*	`conf`	An Uncertainty Principle is a Price of Privacy-Preserving Microdata. NeurIPS John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson L. Garfinkel, Daniel Kifer, Philip Leclerc, William Sexton, Ashley Simpson, Christine Task, Pavel Zhuravlev
2021	J	`jnl`	An Uncertainty Principle is a Price of Privacy-Preserving Microdata. CoRR John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson L. Garfinkel, Daniel Kifer, Philip Leclerc, William Sexton, Ashley Simpson, Christine Task, Pavel Zhuravlev
2021	A*	`conf`	DPGen: Automated Program Synthesis for Differential Privacy. CCS Yuxin Wang, Zeyu Ding, Yingtai Xiao, Daniel Kifer, Danfeng Zhang
2021	J	`jnl`	DPGen: Automated Program Synthesis for Differential Privacy. CoRR Yuxin Wang, Zeyu Ding, Yingtai Xiao, Daniel Kifer, Danfeng Zhang
2021	—	`conf`	Investigating Backpropagation Alternatives when Learning to Dynamically Count with Recurrent Neural Networks. ICGI Ankur Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
2021	—	`conf`	OmniLayout: Room Layout Reconstruction From Indoor Spherical Panoramas. CVPR Workshops Shivansh Rao, Vikas Kumar, Daniel Kifer, C. Lee Giles, Ankur Mali
2021	J	`jnl`	OmniLayout: Room Layout Reconstruction from Indoor Spherical Panoramas. CoRR Shivansh Rao, Vikas Kumar, Daniel Kifer, C. Lee Giles, Ankur Mali
2021	J	`jnl`	Optimizing Fitness-For-Use of Differentially Private Linear Queries. Proc. VLDB Endow. Yingtai Xiao, Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer
2021	—	`conf`	Recognizing Long Grammatical Sequences using Recurrent Networks Augmented with an External Differentiable Stack. ICGI Ankur Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
2021	A*	`conf`	Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units. AAAI Ankur Mali, Alexander G. Ororbia II, Daniel Kifer, C. Lee Giles
2021	J	`jnl`	Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units. CoRR Ankur Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
2021	J	`jnl`	Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping. Proc. Priv. Enhancing Technol. Jaewoo Lee, Daniel Kifer
2021	J	`jnl`	The Permute-and-Flip Mechanism is Identical to Report-Noisy-Max with Exponential Noise. CoRR Zeyu Ding, Daniel Kifer, Sayed M. Saghaian N. E., Thomas Steinke, Yuxin Wang, Yingtai Xiao, Danfeng Zhang
2021	J	`jnl`	The data synergy effects of time-series deep learning models in hydrology. CoRR Kuai Fang, Daniel Kifer, Kathryn Lawson, Dapeng Feng, Chaopeng Shen
2020	A*	`conf`	CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples. CCS Yuxin Wang, Zeyu Ding, Daniel Kifer, Danfeng Zhang
2020	J	`jnl`	CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples. CoRR Yuxin Wang, Zeyu Ding, Daniel Kifer, Danfeng Zhang
2020	J	`jnl`	Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations. IEEE Trans. Neural Networks Learn. Syst. Alexander Ororbia, Ankur Mali, C. Lee Giles, Daniel Kifer
2020	J	`jnl`	Differentially Private Deep Learning with Direct Feedback Alignment. CoRR Jaewoo Lee, Daniel Kifer
2020	A	`conf`	Follow The Curve: Arbitrarily Oriented Scene Text Detection Using Key Points Spotting And Curve Prediction. ICME Ke Yuan, Dafang He, Xiao Yang, Zhi Tang, Daniel Kifer, C. Lee Giles
2020	J	`jnl`	Free Gap Estimates from the Exponential Mechanism, Sparse Vector, Noisy Max and Related Algorithms. CoRR Zeyu Ding, Yuxin Wang, Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer
2020	J	`jnl`	Guidelines for Implementing and Auditing Differentially Private Systems. CoRR Daniel Kifer, Solomon Messing, Aaron Roth, Abhradeep Thakurta, Danfeng Zhang
2020	J	`jnl`	Optimizing Fitness-For-Use of Differentially Private Linear Queries. CoRR Yingtai Xiao, Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer
2020	J	`jnl`	Recognizing Long Grammatical Sequences Using Recurrent Networks Augmented With An External Differentiable Stack. CoRR Ankur Mali, Alexander Ororbia, Daniel Kifer, Clyde Lee Giles
2020	J	`jnl`	Reducing the Computational Burden of Deep Learning with Recursive Local Representation Alignment. CoRR Alexander Ororbia, Ankur Mali, Daniel Kifer, C. Lee Giles
2020	J	`jnl`	Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping. CoRR Jaewoo Lee, Daniel Kifer
2020	J	`jnl`	The Neural Coding Framework for Learning Generative Models. CoRR Alexander Ororbia, Daniel Kifer
2019	A	`conf`	A Learning-based Text Synthesis Engine for Scene Text Detection. BMVC Xiao Yang, Dafang He, Daniel Kifer, C. Lee Giles
2019	J	`jnl`	A Simple Baseline for Travel Time Estimation using Large-scale Trip Data. ACM Trans. Intell. Syst. Technol. Hongjian Wang, Xianfeng Tang, Yu-Hsuan Kuo, Daniel Kifer, Zhenhui Li
2019	A*	`conf`	Adversarial Training for Community Question Answer Selection Based on Multi-Scale Matching. AAAI Xiao Yang, Madian Khabsa, Miaosen Wang, Wei Wang, Ahmed Hassan Awadallah, Daniel Kifer, C. Lee Giles
2019	J	`jnl`	Differentially Private Confidence Intervals for Empirical Risk Minimization. J. Priv. Confidentiality Yue Wang, Daniel Kifer, Jaewoo Lee
2019	A*	`conf`	ET-Lasso: A New Efficient Tuning of Lasso-type Regularization for High-Dimensional Data. KDD Songshan Yang, Jiawei Wen, Xiang Zhan, Daniel Kifer
2019	J	`jnl`	Evaluating aleatoric and epistemic uncertainties of time series deep learning models for soil moisture predictions. CoRR Kuai Fang, Chaopeng Shen, Daniel Kifer
2019	J	`jnl`	Free Gap Information from the Differentially Private Sparse Vector and Noisy Max Mechanisms. CoRR Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer
2019	J	`jnl`	Lifelong Neural Predictive Coding: Sparsity Yields Less Forgetting when Learning Cumulatively. CoRR Alexander Ororbia, Ankur Mali, Daniel Kifer, C. Lee Giles
2019	J	`jnl`	Non-Stationary Model for Crime Rate Inference Using Modern Urban Data. IEEE Trans. Big Data Hongjian Wang, Huaxiu Yao, Daniel Kifer, Corina Graif, Zhenhui Li
2019	J	`jnl`	Proving Differential Privacy with Shadow Execution. CoRR Yuxin Wang, Zeyu Ding, Guanhong Wang, Daniel Kifer, Danfeng Zhang
2019	A*	`conf`	Proving differential privacy with shadow execution. PLDI Yuxin Wang, Zeyu Ding, Guanhong Wang, Daniel Kifer, Danfeng Zhang
2018	—	`ch.`	Change Detection on Streams. Encyclopedia of Database Systems (2nd ed.) Daniel Kifer
2018	A*	`conf`	Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget. KDD Jaewoo Lee, Daniel Kifer
2018	J	`jnl`	Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget. CoRR Jaewoo Lee, Daniel Kifer
2018	J	`jnl`	Conducting Credit Assignment by Aligning Local Representations. CoRR Alexander G. Ororbia II, Ankur Mali, Daniel Kifer, C. Lee Giles
2018	A	`conf`	Detecting Outliers in Data with Correlated Measures. CIKM Yu-Hsuan Kuo, Zhenhui Li, Daniel Kifer
2018	J	`jnl`	Detecting Outliers in Data with Correlated Measures. CoRR Yu-Hsuan Kuo, Zhenhui Li, Daniel Kifer
2018	A*	`conf`	Detecting Violations of Differential Privacy. CCS Zeyu Ding, Yuxin Wang, Guanhong Wang, Danfeng Zhang, Daniel Kifer
2018	J	`jnl`	Differentially Private Confidence Intervals for Empirical Risk Minimization. CoRR Yue Wang, Daniel Kifer, Jaewoo Lee
2018	J	`jnl`	Differentially Private Hierarchical Count-of-Counts Histograms. Proc. VLDB Endow. Yu-Hsuan Kuo, Cho-Chun Chiu, Daniel Kifer, Michael Hay, Ashwin Machanavajjhala
2018	J	`jnl`	Differentially Private Hierarchical Group Size Estimation. CoRR Yu-Hsuan Kuo, Cho-Chun Chiu, Daniel Kifer, Michael Hay, Ashwin Machanavajjhala
2018	J	`jnl`	ET-Lasso: Efficient Tuning of Lasso for High-Dimensional Data. CoRR Songshan Yang, Jiawei Wen, Xiang Zhan, Daniel Kifer
2018	J	`jnl`	Guided Attention for Large Scale Scene Text Verification. CoRR Dafang He, Yeqing Li, Alexander N. Gorban, Derrall Heath, Julian Ibarz, Qian Yu, Daniel Kifer, C. Lee Giles
2018	—	`conf`	Large Scale Scene Text Verification with Guided Attention. ACCV (5) Dafang He, Yeqing Li, Alexander N. Gorban, Derrall Heath, Julian Ibarz, Qian Yu, Daniel Kifer, C. Lee Giles
2018	J	`jnl`	Online Learning of Recurrent Neural Architectures by Locally Aligning Distributed Representations. CoRR Alexander Ororbia, Ankur Mali, C. Lee Giles, Daniel Kifer
2018	J	`jnl`	Statistical Approximating Distributions Under Differential Privacy. J. Priv. Confidentiality Yue Wang, Daniel Kifer, Jaewoo Lee, Vishesh Karwa
2018	J	`jnl`	TextContourNet: a Flexible and Effective Framework for Improving Scene Text Detection Architecture with a Multi-task Cascade. CoRR Dafang He, Xiao Yang, Daniel Kifer, C. Lee Giles
2018	J	`jnl`	Toward Detecting Violations of Differential Privacy. CoRR Ding Ding, Yuxin Wang, Guanhong Wang, Danfeng Zhang, Daniel Kifer
2017	A	`conf`	A New Class of Private Chi-Square Hypothesis Tests. AISTATS Ryan Rogers, Daniel Kifer
2017	A	`conf`	Improving Offline Handwritten Chinese Character Recognition by Iterative Refinement. ICDAR Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles
2017	J	`jnl`	Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Network. CoRR Xiao Yang, Mehmet Ersin Yümer, Paul Asente, Mike Kraley, Daniel Kifer, C. Lee Giles
2017	A*	`conf`	Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Networks. CVPR Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, C. Lee Giles
2017	A*	`conf`	Learning to Read Irregular Text with Attention Mechanisms. IJCAI Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles
2017	A*	`conf`	LightDP: towards automating differential privacy proofs. POPL Danfeng Zhang, Daniel Kifer
2017	A	`conf`	Multi-Scale Multi-Task FCN for Semantic Page Segmentation and Table Detection. ICDAR Dafang He, Scott Cohen, Brian L. Price, Daniel Kifer, C. Lee Giles
2017	A*	`conf`	Multi-scale FCN with Cascaded Instance Aware Segmentation for Arbitrary Oriented Word Spotting in the Wild. CVPR Dafang He, Xiao Yang, Chen Liang, Zihan Zhou, Alexander G. Ororbia II, Daniel Kifer, C. Lee Giles
2017	A*	`conf`	Predicting Demographics of High-Resolution Geographies with Geotagged Tweets. AAAI Omar Montasser, Daniel Kifer
2017	J	`jnl`	Predicting Demographics of High-Resolution Geographies with Geotagged Tweets. CoRR Omar Montasser, Daniel Kifer
2017	—	`conf`	Smart Library: Identifying Books on Library Shelves Using Supervised Deep Learning for Scene Text Reading. JCDL Xiao Yang, Dafang He, Wenyi Huang, Alexander Ororbia, Zihan Zhou, Daniel Kifer, C. Lee Giles
2017	J	`jnl`	Unifying Adversarial Training Algorithms with Data Gradient Regularization. Neural Comput. Alexander G. Ororbia II, Daniel Kifer, C. Lee Giles
2016	J	`jnl`	A New Class of Private Chi-Square Tests. CoRR Daniel Kifer, Ryan Rogers
2016	—	`conf`	A simple baseline for travel time estimation using large-scale trip data. SIGSPATIAL/GIS Hongjian Wang, Yu-Hsuan Kuo, Daniel Kifer, Zhenhui Li
2016	—	`conf`	Aggregating Local Context for Accurate Scene Text Detection. ACCV (5) Dafang He, Xiao Yang, Wenyi Huang, Zihan Zhou, Daniel Kifer, C. Lee Giles
2016	J	`jnl`	AutoPriv: Automating Differential Privacy Proofs. CoRR Danfeng Zhang, Daniel Kifer
2016	A*	`conf`	Crime Rate Inference with Big Data. KDD Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li
2016	A*	`conf`	Detecting Arbitrary Oriented Text in the Wild with a Visual Attention Model. ACM Multimedia Wenyi Huang, Dafang He, Xiao Yang, Zihan Zhou, Daniel Kifer, C. Lee Giles
2016	J	`jnl`	Postprocessing for Iterative Differentially Private Algorithms. CoRR Jaewoo Lee, Daniel Kifer
2016	J	`jnl`	Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization. CoRR Alexander G. Ororbia II, C. Lee Giles, Daniel Kifer
2015	J	`jnl`	Designing statistical privacy for your data. Commun. ACM Ashwin Machanavajjhala, Daniel Kifer
2015	J	`jnl`	Differentially Private Hypothesis Testing, Revisited. CoRR Yue Wang, Jaewoo Lee, Daniel Kifer
2015	J	`jnl`	Information Measures in Statistical Privacy and Data Processing Applications. ACM Trans. Knowl. Discov. Data Bing-Rong Lin, Daniel Kifer
2015	A*	`conf`	Maximum Likelihood Postprocessing for Differential Privacy under Consistency Constraints. KDD Jaewoo Lee, Yue Wang, Daniel Kifer
2015	A*	`conf`	On Estimating the Swapping Rate for Categorical Data. KDD Daniel Kifer
2015	A*	`conf`	Privacy and the Price of Data. LICS Daniel Kifer
2014	J	`jnl`	On Arbitrage-free Pricing for General Data Queries. Proc. VLDB Endow. Bing-Rong Lin, Daniel Kifer
2014	J	`jnl`	Pufferfish: A framework for mathematical privacy definitions. ACM Trans. Database Syst. Daniel Kifer, Ashwin Machanavajjhala
2013	A	`conf`	Extraction of statistically significant malware behaviors. ACSAC Sirinda Palahan, Domagoj Babic, Swarat Chaudhuri, Daniel Kifer
2013	—	`conf`	Geometry of privacy and utility. GlobalSIP Bing-Rong Lin, Daniel Kifer
2013	—	`conf`	Information preservation in statistical privacy and bayesian estimation of unattributed histograms. SIGMOD Conference Bing-Rong Lin, Daniel Kifer
2012	J	`jnl`	A Framework for Extracting Semantic Guarantees from Privacy CoRR Bing-Rong Lin, Daniel Kifer
2012	A*	`conf`	A rigorous and customizable framework for privacy. PODS Daniel Kifer, Ashwin Machanavajjhala
2012	J	`jnl`	An Axiomatic View of Statistical Privacy and Utility. J. Priv. Confidentiality Daniel Kifer, Bing-Rong Lin
2012	A*	`conf`	Private Convex Optimization for Empirical Risk Minimization with Applications to High-dimensional Regression. COLT Daniel Kifer, Adam D. Smith, Abhradeep Thakurta
2012	—	`conf`	Reasoning about privacy using axioms. ACSCC Bing-Rong Lin, Daniel Kifer
2011	A	`conf`	Citation recommendation without author supervision. WSDM Qi He, Daniel Kifer, Jian Pei, Prasenjit Mitra, C. Lee Giles
2011	—	`conf`	No free lunch in data privacy. SIGMOD Conference Daniel Kifer, Ashwin Machanavajjhala
2010	A*	`conf`	Context-aware citation recommendation. WWW Qi He, Jian Pei, Daniel Kifer, Prasenjit Mitra, C. Lee Giles
2010	A*	`conf`	Privacy in data publishing. ICDE Johannes Gehrke, Daniel Kifer, Ashwin Machanavajjhala
2010	A*	`conf`	Towards an axiomatization of statistical privacy and utility. PODS Daniel Kifer, Bing-Rong Lin
2010	A*	`conf`	What Is an Opinion About? Exploring Political Standpoints Using Opinion Scoring Model. AAAI Bi Chen, Leilei Zhu, Daniel Kifer, Dongwon Lee
2009	—	`conf`	Attacks on privacy and deFinetti's theorem. SIGMOD Conference Daniel Kifer
2009	—	`ch.`	Change Detection on Streams. Encyclopedia of Database Systems Daniel Kifer
2009	J	`jnl`	Privacy-Preserving Data Publishing. Found. Trends Databases Bee-Chung Chen, Daniel Kifer, Kristen LeFevre, Ashwin Machanavajjhala
2008	A*	`conf`	Privacy: Theory meets Practice on the Map. ICDE Ashwin Machanavajjhala, Daniel Kifer, John M. Abowd, Johannes Gehrke, Lars Vilhuber
2008	J	`jnl`	Scheduling shared scans of large data files. Proc. VLDB Endow. Parag Agrawal, Daniel Kifer, Christopher Olston
2007	J	`jnl`	Worst-Case Background Knowledge for Privacy-Preserving Data Publishing CoRR David J. Martin, Daniel Kifer, Ashwin Machanavajjhala, Johannes Gehrke, Joseph Y. Halpern
2007	A*	`conf`	Worst-Case Background Knowledge for Privacy-Preserving Data Publishing. ICDE David J. Martin, Daniel Kifer, Ashwin Machanavajjhala, Johannes Gehrke, Joseph Y. Halpern
2006	—	`conf`	Injecting utility into anonymized datasets. SIGMOD Conference Daniel Kifer, Johannes Gehrke
2006	A*	`conf`	l-Diversity: Privacy Beyond k-Anonymity. ICDE Ashwin Machanavajjhala, Johannes Gehrke, Daniel Kifer, Muthuramakrishnan Venkitasubramaniam
2004	J	`jnl`	A Vision for PetaByte Data Management and Analyis Services for the Arecibo Telescope. IEEE Data Eng. Bull. Manuel Calimlim, Jim Cordes, Alan J. Demers, Julia Deneva, Johannes Gehrke, Daniel Kifer, Mirek Riedewald, Jayavel Shanmugasundaram
2004	A*	`conf`	Detecting Change in Data Streams. VLDB Daniel Kifer, Shai Ben-David, Johannes Gehrke
2004	—	`conf`	How to Quickly Find a Witness. Constraint-Based Mining and Inductive Databases Daniel Kifer, Johannes Gehrke, Cristian Bucila, Walker M. White
2003	J	`jnl`	DualMiner: A Dual-Pruning Algorithm for Itemsets with Constraints. Data Min. Knowl. Discov. Cristian Bucila, Johannes Gehrke, Daniel Kifer, Walker M. White
2003	A*	`conf`	How to quickly find a witness. PODS Daniel Kifer, Johannes Gehrke, Cristian Bucila, Walker M. White
2002	A*	`conf`	DualMiner: a dual-pruning algorithm for itemsets with constraints. KDD Cristian Bucila, Johannes Gehrke, Daniel Kifer, Walker M. White