DualMiner: A Dual-Pruning Algorithm for Itemsets with Constraints. - Cristian Bucila; Johannes Gehrke; Daniel Kifer; Walker M. White (Data Min. Knowl. Discov., 2003)

How to Quickly Find a Witness. - Daniel Kifer; Johannes Gehrke; Cristian Bucila; Walker M. White (Constraint-Based Mining and Inductive Databases, 2004)

Detecting Change in Data Streams. - Daniel Kifer; Shai Ben-David; Johannes Gehrke (VLDB, 2004)

A Vision for PetaByte Data Management and Analyis Services for the Arecibo Telescope. - Manuel Calimlim; Jim Cordes; Alan J. Demers; Julia Deneva; Johannes Gehrke; Daniel Kifer; Mirek Riedewald; Jayavel Shanmugasundaram (IEEE Data Eng. Bull., 2004)

l-Diversity: Privacy Beyond k-Anonymity. - Ashwin Machanavajjhala; Johannes Gehrke; Daniel Kifer; Muthuramakrishnan Venkitasubramaniam (ICDE, 2006)

Injecting utility into anonymized datasets. - Daniel Kifer; Johannes Gehrke (SIGMOD Conference, 2006)

Graphs and Privacy. - Dan Kifer (2006)

Worst-Case Background Knowledge for Privacy-Preserving Data Publishing. - David J. Martin 001; Daniel Kifer; Ashwin Machanavajjhala; Johannes Gehrke; Joseph Y. Halpern (ICDE, 2007)

L-diversity: Privacy beyond k-anonymity. - Ashwin Machanavajjhala; Daniel Kifer; Johannes Gehrke; Muthuramakrishnan Venkitasubramaniam (ACM Trans. Knowl. Discov. Data, 2007)

Privacy: Theory meets Practice on the Map. - Ashwin Machanavajjhala; Daniel Kifer; John M. Abowd; Johannes Gehrke; Lars Vilhuber (ICDE, 2008)

Scheduling shared scans of large data files. - Parag Agrawal; Daniel Kifer; Christopher Olston (Proc. VLDB Endow., 2008)

Attacks on privacy and deFinetti's theorem. - Daniel Kifer (SIGMOD Conference, 2009)

Privacy-Preserving Data Publishing. - Bee-Chung Chen; Daniel Kifer; Kristen LeFevre; Ashwin Machanavajjhala (Found. Trends Databases, 2009)

Change Detection on Streams. - Daniel Kifer (Encyclopedia of Database Systems, 2009)

What Is an Opinion About? Exploring Political Standpoints Using Opinion Scoring Model. - Bi Chen; Leilei Zhu; Daniel Kifer; Dongwon Lee 001 (AAAI, 2010)

Privacy in data publishing. - Johannes Gehrke; Daniel Kifer; Ashwin Machanavajjhala (ICDE, 2010)

Towards an axiomatization of statistical privacy and utility. - Daniel Kifer; Bing-Rong Lin (PODS, 2010)

Context-aware citation recommendation. - Qi He 002; Jian Pei 001; Daniel Kifer; Prasenjit Mitra; C. Lee Giles (WWW, 2010)

No free lunch in data privacy. - Daniel Kifer; Ashwin Machanavajjhala (SIGMOD Conference, 2011)

Citation recommendation without author supervision. - Qi He 002; Daniel Kifer; Jian Pei 001; Prasenjit Mitra; C. Lee Giles (WSDM, 2011)

Reasoning about privacy using axioms. - Bing-Rong Lin; Daniel Kifer (ACSCC, 2012)

A rigorous and customizable framework for privacy. - Daniel Kifer; Ashwin Machanavajjhala (PODS, 2012)

A Framework for Extracting Semantic Guarantees from Privacy - Bing-Rong Lin; Daniel Kifer (CoRR, 2012)

Private Convex Optimization for Empirical Risk Minimization with Applications to High-dimensional Regression. - Daniel Kifer; Adam D. Smith 001; Abhradeep Thakurta (COLT, 2012)

An Axiomatic View of Statistical Privacy and Utility. - Daniel Kifer; Bing-Rong Lin (J. Priv. Confidentiality, 2012)

Extraction of statistically significant malware behaviors. - Sirinda Palahan; Domagoj Babic; Swarat Chaudhuri; Daniel Kifer (ACSAC, 2013)

Geometry of privacy and utility. - Bing-Rong Lin; Daniel Kifer (GlobalSIP, 2013)

Information preservation in statistical privacy and bayesian estimation of unattributed histograms. - Bing-Rong Lin; Daniel Kifer (SIGMOD Conference, 2013)

Introduction to Special Section. - Dan Kifer (J. Priv. Confidentiality, 2013)

Towards a Systematic Analysis of Privacy Definitions. - Bing-Rong Lin; Dan Kifer (J. Priv. Confidentiality, 2014)

On Arbitrage-free Pricing for General Data Queries. - Bing-Rong Lin; Daniel Kifer (Proc. VLDB Endow., 2014)

Pufferfish: A framework for mathematical privacy definitions. - Daniel Kifer; Ashwin Machanavajjhala (ACM Trans. Database Syst., 2014)

On Estimating the Swapping Rate for Categorical Data. - Daniel Kifer (KDD, 2015)

Maximum Likelihood Postprocessing for Differential Privacy under Consistency Constraints. - Jaewoo Lee; Yue Wang; Daniel Kifer (KDD, 2015)

Privacy and the Price of Data. - Daniel Kifer (LICS, 2015)

Designing statistical privacy for your data. - Ashwin Machanavajjhala; Daniel Kifer (Commun. ACM, 2015)

Private Posterior distributions from Variational approximations. - Vishesh Karwa; Dan Kifer; Aleksandra B. Slavkovic (CoRR, 2015)

Differentially Private Hypothesis Testing, Revisited. - Yue Wang; Jaewoo Lee; Daniel Kifer (CoRR, 2015)

Information Measures in Statistical Privacy and Data Processing Applications. - Bing-Rong Lin; Daniel Kifer (ACM Trans. Knowl. Discov. Data, 2015)

Aggregating Local Context for Accurate Scene Text Detection. - Dafang He; Xiao Yang 004; Wenyi Huang; Zihan Zhou 001; Daniel Kifer; C. Lee Giles (ACCV (5), 2016)

A simple baseline for travel time estimation using large-scale trip data. - Hongjian Wang 002; Yu-Hsuan Kuo; Daniel Kifer; Zhenhui Li (SIGSPATIAL/GIS, 2016)

Crime Rate Inference with Big Data. - Hongjian Wang 002; Daniel Kifer; Corina Graif; Zhenhui Li (KDD, 2016)

Detecting Arbitrary Oriented Text in the Wild with a Visual Attention Model. - Wenyi Huang; Dafang He; Xiao Yang 004; Zihan Zhou 001; Daniel Kifer; C. Lee Giles (ACM Multimedia, 2016)

A New Class of Private Chi-Square Tests. - Daniel Kifer; Ryan Rogers 002 (CoRR, 2016)

Postprocessing for Iterative Differentially Private Algorithms. - Jaewoo Lee; Daniel Kifer (CoRR, 2016)

Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization. - Alexander G. Ororbia II; C. Lee Giles; Daniel Kifer (CoRR, 2016)

Smart Library: Identifying Books in a Library using Richly Supervised Deep Scene Text Reading. - Xiao Yang 004; Dafang He; Wenyi Huang; Zihan Zhou 001; Alexander Ororbia; Dan Kifer; C. Lee Giles (CoRR, 2016)

AutoPriv: Automating Differential Privacy Proofs. - Danfeng Zhang; Daniel Kifer (CoRR, 2016)

Predicting Demographics of High-Resolution Geographies with Geotagged Tweets. - Omar Montasser; Daniel Kifer (AAAI, 2017)

A New Class of Private Chi-Square Hypothesis Tests. - Ryan Rogers 002; Daniel Kifer (AISTATS, 2017)

Multi-scale FCN with Cascaded Instance Aware Segmentation for Arbitrary Oriented Word Spotting in the Wild. - Dafang He; Xiao Yang 004; Chen Liang 001; Zihan Zhou 001; Alexander G. Ororbia II; Daniel Kifer; C. Lee Giles (CVPR, 2017)

Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Networks. - Xiao Yang 004; Ersin Yumer; Paul Asente; Mike Kraley; Daniel Kifer; C. Lee Giles (CVPR, 2017)

Multi-Scale Multi-Task FCN for Semantic Page Segmentation and Table Detection. - Dafang He; Scott Cohen; Brian L. Price; Daniel Kifer; C. Lee Giles (ICDAR, 2017)

Improving Offline Handwritten Chinese Character Recognition by Iterative Refinement. - Xiao Yang 004; Dafang He; Zihan Zhou 001; Daniel Kifer; C. Lee Giles (ICDAR, 2017)

Learning to Read Irregular Text with Attention Mechanisms. - Xiao Yang 004; Dafang He; Zihan Zhou 001; Daniel Kifer; C. Lee Giles (IJCAI, 2017)

Smart Library: Identifying Books on Library Shelves Using Supervised Deep Learning for Scene Text Reading. - Xiao Yang 004; Dafang He; Wenyi Huang; Alexander Ororbia; Zihan Zhou 001; Daniel Kifer; C. Lee Giles (JCDL, 2017)

LightDP: towards automating differential privacy proofs. - Danfeng Zhang; Daniel Kifer (POPL, 2017)

Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Network. - Xiao Yang 004; Mehmet Ersin Yümer 001; Paul Asente; Mike Kraley; Daniel Kifer; C. Lee Giles (CoRR, 2017)

Unifying Adversarial Training Algorithms with Data Gradient Regularization. - Alexander G. Ororbia II; Daniel Kifer; C. Lee Giles (Neural Comput., 2017)

Large Scale Scene Text Verification with Guided Attention. - Dafang He; Yeqing Li; Alexander N. Gorban; Derrall Heath; Julian Ibarz; Qian Yu; Daniel Kifer; C. Lee Giles (ACCV (5), 2018)

Detecting Violations of Differential Privacy. - Zeyu Ding 001; Yuxin Wang 004; Guanhong Wang; Danfeng Zhang; Daniel Kifer (CCS, 2018)

Detecting Outliers in Data with Correlated Measures. - Yu-Hsuan Kuo; Zhenhui Li; Daniel Kifer (CIKM, 2018)

Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget. - Jaewoo Lee; Daniel Kifer (KDD, 2018)

Conducting Credit Assignment by Aligning Local Representations. - Alexander G. Ororbia II; Ankur Arjun Mali; Daniel Kifer; C. Lee Giles (CoRR, 2018)

Differentially Private Hierarchical Group Size Estimation. - Yu-Hsuan Kuo; Cho-Chun Chiu; Daniel Kifer; Michael Hay; Ashwin Machanavajjhala (CoRR, 2018)

Guided Attention for Large Scale Scene Text Verification. - Dafang He; Yeqing Li; Alexander N. Gorban; Derrall Heath; Julian Ibarz; Qian Yu; Daniel Kifer; C. Lee Giles (CoRR, 2018)

Toward Detecting Violations of Differential Privacy. - Ding Ding; Yuxin Wang 004; Guanhong Wang; Danfeng Zhang; Daniel Kifer (CoRR, 2018)

ET-Lasso: Efficient Tuning of Lasso for High-Dimensional Data. - Songshan Yang; Jiawei Wen; Xiang Zhan; Daniel Kifer (CoRR, 2018)

Online Learning of Recurrent Neural Architectures by Locally Aligning Distributed Representations. - Alexander Ororbia; Ankur Arjun Mali; C. Lee Giles; Daniel Kifer (CoRR, 2018)

Reminiscenses of Steve Fienberg. - Dan Kifer (J. Priv. Confidentiality, 2018)

Statistical Approximating Distributions Under Differential Privacy. - Yue Wang; Daniel Kifer; Jaewoo Lee; Vishesh Karwa (J. Priv. Confidentiality, 2018)

Differentially Private Hierarchical Count-of-Counts Histograms. - Yu-Hsuan Kuo; Cho-Chun Chiu; Daniel Kifer; Michael Hay; Ashwin Machanavajjhala (Proc. VLDB Endow., 2018)

Change Detection on Streams. - Daniel Kifer (Encyclopedia of Database Systems (2nd ed.), 2018)

Adversarial Training for Community Question Answer Selection Based on Multi-Scale Matching. - Xiao Yang 004; Madian Khabsa; Miaosen Wang; Wei Wang 238; Ahmed Hassan Awadallah; Daniel Kifer; C. Lee Giles (AAAI, 2019)

Renyi Differentially Private ERM for Smooth Objectives. - Chen Chen; Jaewoo Lee; Dan Kifer (AISTATS, 2019)

A Learning-based Text Synthesis Engine for Scene Text Detection. - Xiao Yang 010; Dafang He; Daniel Kifer; C. Lee Giles (BMVC, 2019)

A Neural Temporal Model for Human Motion Prediction. - Anand Gopalakrishnan; Ankur Arjun Mali; Dan Kifer; C. Lee Giles; Alexander G. Ororbia II (CVPR, 2019)

ET-Lasso: A New Efficient Tuning of Lasso-type Regularization for High-Dimensional Data. - Songshan Yang; Jiawei Wen; Xiang Zhan; Daniel Kifer (KDD, 2019)

Proving differential privacy with shadow execution. - Yuxin Wang 004; Zeyu Ding 001; Guanhong Wang; Daniel Kifer; Danfeng Zhang (PLDI, 2019)

TextContourNet: A Flexible and Effective Framework for Improving Scene Text Detection Architecture With a Multi-Task Cascade. - Dafang He; Xiao Yang 004; Dan Kifer; C. Lee Giles (WACV, 2019)

Lifelong Neural Predictive Coding: Sparsity Yields Less Forgetting when Learning Cumulatively. - Alexander Ororbia; Ankur Arjun Mali; Daniel Kifer; C. Lee Giles (CoRR, 2019)

Evaluating aleatoric and epistemic uncertainties of time series deep learning models for soil moisture predictions. - Kuai Fang; Chaopeng Shen; Daniel Kifer (CoRR, 2019)

Differentially Private Confidence Intervals for Empirical Risk Minimization. - Yue Wang; Daniel Kifer; Jaewoo Lee (J. Priv. Confidentiality, 2019)

Free Gap Information from the Differentially Private Sparse Vector and Noisy Max Mechanisms. - Zeyu Ding 001; Yuxin Wang 004; Danfeng Zhang; Dan Kifer (Proc. VLDB Endow., 2019)

Non-Stationary Model for Crime Rate Inference Using Modern Urban Data. - Hongjian Wang 002; Huaxiu Yao; Daniel Kifer; Corina Graif; Zhenhui Li (IEEE Trans. Big Data, 2019)

A Simple Baseline for Travel Time Estimation using Large-scale Trip Data. - Hongjian Wang 002; Xianfeng Tang; Yu-Hsuan Kuo; Daniel Kifer; Zhenhui Li (ACM Trans. Intell. Syst. Technol., 2019)

CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples. - Yuxin Wang 004; Zeyu Ding 001; Daniel Kifer; Danfeng Zhang (CCS, 2020)

Follow The Curve: Arbitrarily Oriented Scene Text Detection Using Key Points Spotting And Curve Prediction. - Ke Yuan; Dafang He; Xiao Yang 004; Zhi Tang 001; Daniel Kifer; C. Lee Giles (ICME, 2020)

Reducing the Computational Burden of Deep Learning with Recursive Local Representation Alignment. - Alexander Ororbia; Ankur Arjun Mali; Daniel Kifer; C. Lee Giles (CoRR, 2020)

Guidelines for Implementing and Auditing Differentially Private Systems. - Daniel Kifer; Solomon Messing; Aaron Roth 001; Abhradeep Thakurta; Danfeng Zhang (CoRR, 2020)

Differentially Private Deep Learning with Direct Feedback Alignment. - Jaewoo Lee; Daniel Kifer (CoRR, 2020)

The Neural Coding Framework for Learning Generative Models. - Alexander Ororbia; Daniel Kifer (CoRR, 2020)

Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations. - Alexander Ororbia; Ankur Arjun Mali; C. Lee Giles; Daniel Kifer (IEEE Trans. Neural Networks Learn. Syst., 2020)

Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units. - Ankur Arjun Mali; Alexander G. Ororbia II; Daniel Kifer; C. Lee Giles (AAAI, 2021)

DPGen: Automated Program Synthesis for Differential Privacy. - Yuxin Wang 004; Zeyu Ding 001; Yingtai Xiao; Daniel Kifer; Danfeng Zhang (CCS, 2021)

OmniLayout: Room Layout Reconstruction From Indoor Spherical Panoramas. - Shivansh Rao; Vikas Kumar; Daniel Kifer; C. Lee Giles; Ankur Arjun Mali (CVPR Workshops, 2021)

An Empirical Analysis of Recurrent Learning Algorithms in Neural Lossy Image Compression Systems. - Ankur Arjun Mali; Alexander G. Ororbia II; Dan Kifer; C. Lee Giles (DCC, 2021)

Recognizing Long Grammatical Sequences using Recurrent Networks Augmented with an External Differentiable Stack. - Ankur Arjun Mali; Alexander Ororbia; Daniel Kifer; C. Lee Giles (ICGI, 2021)

Investigating Backpropagation Alternatives when Learning to Dynamically Count with Recurrent Neural Networks. - Ankur Arjun Mali; Alexander Ororbia; Daniel Kifer; C. Lee Giles (ICGI, 2021)

An Uncertainty Principle is a Price of Privacy-Preserving Microdata. - John M. Abowd; Robert Ashmead; Ryan Cumings-Menon; Simson L. Garfinkel; Daniel Kifer; Philip Leclerc; William Sexton; Ashley Simpson; Christine Task; Pavel Zhuravlev (NeurIPS, 2021)

The data synergy effects of time-series deep learning models in hydrology. - Kuai Fang; Daniel Kifer; Kathryn Lawson; Dapeng Feng; Chaopeng Shen (CoRR, 2021)

The Permute-and-Flip Mechanism is Identical to Report-Noisy-Max with Exponential Noise. - Zeyu Ding 001; Daniel Kifer; Sayed M. Saghaian N. E.; Thomas Steinke 002; Yuxin Wang 004; Yingtai Xiao; Danfeng Zhang (CoRR, 2021)

Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping. - Jaewoo Lee; Daniel Kifer (Proc. Priv. Enhancing Technol., 2021)

Optimizing Fitness-For-Use of Differentially Private Linear Queries. - Yingtai Xiao; Zeyu Ding 001; Yuxin Wang 004; Danfeng Zhang; Daniel Kifer (Proc. VLDB Endow., 2021)

Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder. - Ankur Arjun Mali; Alexander G. Ororbia II; Daniel Kifer; C. Lee Giles (DCC, 2022)

Lifelong Neural Predictive Coding: Learning Cumulatively Online without Forgetting. - Alexander Ororbia; Ankur Arjun Mali; C. Lee Giles; Daniel Kifer (NeurIPS, 2022)

Geographic Spines in the 2020 Census Disclosure Avoidance System TopDown Algorithm. - John M. Abowd; Robert Ashmead; Ryan Cumings-Menon; Daniel Kifer; Philip Leclerc; Jeffrey Ocker; Michael Ratcliffe; Pavel Zhuravlev (CoRR, 2022)

The 2020 Census Disclosure Avoidance System TopDown Algorithm. - 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; et al. (CoRR, 2022)

Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census. - Daniel Kifer; John M. Abowd; Robert Ashmead; Ryan Cumings-Menon; Philip Leclerc; Ashwin Machanavajjhala; William Sexton; Pavel Zhuravlev (CoRR, 2022)

ThreshNet: Segmentation Refinement Inspired by Region-Specific Thresholding. - Savinay Nagendra; Chaopeng Shen; Daniel Kifer (CoRR, 2022)

Constructing a Large-Scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates. - Savinay Nagendra; Daniel Kifer; Benjamin Mirus; Te Pei; Kathryn Lawson; Srikanth Banagere Manjunatha; Weixin Li; Hien Nguyen 003; Tong Qiu; Sarah Tran; Chaopeng Shen (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

Backpropagation-Free Deep Learning with Recursive Local Representation Alignment. - Alexander G. Ororbia II; Ankur Arjun Mali; Daniel Kifer; C. Lee Giles (AAAI, 2023)

An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions. - Yingtai Xiao; Guanlin He; Danfeng Zhang; Daniel Kifer (NeurIPS, 2023)

Differentiable modeling to unify machine learning and physical models and advance Geosciences. - 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; et al. (CoRR, 2023)

A Floating-Point Secure Implementation of the Report Noisy Max with Gap Mechanism. - Zeyu Ding 001; John Durrell; Daniel Kifer; Prottay Protivash; Guanhong Wang; Yuxin Wang 004; Yingtai Xiao; Danfeng Zhang (CoRR, 2023)

On the Tensor Representation and Algebraic Homomorphism of the Neural State Turing Machine. - Ankur Arjun Mali; Alexander Ororbia; Daniel Kifer; C. Lee Giles (CoRR, 2023)

On the Computational Complexity and Formal Hierarchy of Second Order Recurrent Neural Networks. - Ankur Arjun Mali; Alexander Ororbia; Daniel Kifer; C. Lee Giles (CoRR, 2023)

An In-Depth Examination of Requirements for Disclosure Risk Assessment. - 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; et al. (CoRR, 2023)

Estimating Uncertainty in Landslide Segmentation Models. - Savinay Nagendra; Chaopeng Shen; Daniel Kifer (CoRR, 2023)

Disclosure Avoidance for the 2020 Census Demographic and Housing Characteristics File. - Ryan Cumings-Menon; Robert Ashmead; Daniel Kifer; Philip Leclerc; Matthew Spence; Pavel Zhuravlev; John M. Abowd (CoRR, 2023)

The 2010 Census Confidentiality Protections Failed, Here's How and Why. - John M. Abowd; Tamara Adams; Robert Ashmead; David Darais; Sourya Dey; Simson L. Garfinkel; Nathan Goldschlag; Daniel Kifer; Philip Leclerc; Ethan Lew; Scott Moore 001; Rolando A. Rodríguez; et al. (CoRR, 2023)

Answering Private Linear Queries Adaptively using the Common Mechanism. - Yingtai Xiao; Guanhong Wang; Danfeng Zhang; Daniel Kifer (Proc. VLDB Endow., 2023)

Free gap estimates from the exponential mechanism, sparse vector, noisy max and related algorithms. - Zeyu Ding 001; Yuxin Wang 004; Yingtai Xiao; Guanhong Wang; Danfeng Zhang; Daniel Kifer (VLDB J., 2023)

Investigating Symbolic Capabilities of Large Language Models. - Neisarg Dave; Daniel Kifer; C. Lee Giles; Ankur A. Mali (LNSAI@IJCAI, 2024)

Efficient and Private Marginal Reconstruction with Local Non-Negativity. - Brett Mullins; Miguel Fuentes; Yingtai Xiao; Daniel Kifer; Cameron Musco; Daniel R. Sheldon (NeurIPS, 2024)

PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise Binarization. - Savinay Nagendra; Daniel Kifer (WACV, 2024)

Stability Analysis of Various Symbolic Rule Extraction Methods from Recurrent Neural Network. - Neisarg Dave; Daniel Kifer; C. Lee Giles; Ankur A. Mali (CoRR, 2024)

Click Without Compromise: Online Advertising Measurement via Per User Differential Privacy. - Yingtai Xiao; Jian Du; Shikun Zhang; Qiang Yan; Danfeng Zhang; Daniel Kifer (CoRR, 2024)

Precision, Stability, and Generalization: A Comprehensive Assessment of RNNs learnability capability for Classifying Counter and Dyck Languages. - Neisarg Dave; Daniel Kifer; C. Lee Giles; Ankur Arjun Mali (CoRR, 2024)

SAMIC: Segment Anything with In-Context Spatial Prompt Engineering. - Savinay Nagendra; Kashif Rashid; Chaopeng Shen; Daniel Kifer (CoRR, 2024)

Geographic Spines in the 2020 Census Disclosure Avoidance System. - Ryan Cumings-Menon; Robert Ashmead; Daniel Kifer; Philip Leclerc; Jeffrey Ocker; Michael Ratcliffe; Pavel Zhuravlev; John M. Abowd (J. Priv. Confidentiality, 2024)

Reconstruction Attacks on Aggressive Relaxations of Differential Privacy. - Prottay Protivash; John Durrell; Daniel Kifer; Zeyu Ding 001; Danfeng Zhang (J. Priv. Confidentiality, 2024)

Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism. - Arjun Wilkins; Daniel Kifer; Danfeng Zhang; Brian Karrer (J. Priv. Confidentiality, 2024)

Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations. - Abdolmehdi Behroozi; Chaopeng Shen; Daniel Kifer (ICLR, 2025)

Click Without Compromise: Online Advertising Measurement via Per User Differential Privacy. - Yingtai Xiao; Jian Du; Shikun Zhang; Wanrong Zhang 004; Qian Yang; Danfeng Zhang; Daniel Kifer (SP, 2025)