Daniel Kifer

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 105

Top Venues

Publications

Neisarg Dave, Daniel Kifer, C. Lee Giles, Ankur Mali
Stability Analysis of Various Symbolic Rule Extraction Methods from Recurrent Neural Network. CoRR (2024)
Ryan Cumings-Menon, Robert Ashmead, Daniel Kifer, Philip Leclerc, Matthew Spence, Pavel Zhuravlev, John M. Abowd
Disclosure Avoidance for the 2020 Census Demographic and Housing Characteristics File. CoRR (2023)
Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
On the Tensor Representation and Algebraic Homomorphism of the Neural State Turing Machine. CoRR (2023)
Alexander G. Ororbia II, Ankur Arjun Mali, Daniel Kifer, C. Lee Giles
Backpropagation-Free Deep Learning with Recursive Local Representation Alignment. AAAI (2023)
Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
On the Computational Complexity and Formal Hierarchy of Second Order Recurrent Neural Networks. CoRR (2023)
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
An In-Depth Examination of Requirements for Disclosure Risk Assessment. CoRR (2023)
Savinay Nagendra, Chaopeng Shen, Daniel Kifer
Estimating Uncertainty in Landslide Segmentation Models. CoRR (2023)
Zeyu Ding, Yuxin Wang, Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer
Free gap estimates from the exponential mechanism, sparse vector, noisy max and related algorithms. VLDB J. 32 (1) (2023)
Zeyu Ding, John Durrell, Daniel Kifer, Prottay Protivash, Guanhong Wang, Yuxin Wang, Yingtai Xiao, Danfeng Zhang
A Floating-Point Secure Implementation of the Report Noisy Max with Gap Mechanism. CoRR (2023)
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 Clark, Matthew 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
Differentiable modeling to unify machine learning and physical models and advance Geosciences. CoRR (2023)
Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer
Answering Private Linear Queries Adaptively using the Common Mechanism. Proc. VLDB Endow. 16 (8) (2023)
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
The 2010 Census Confidentiality Protections Failed, Here's How and Why. CoRR (2023)
Yingtai Xiao, Guanlin He, Danfeng Zhang, Daniel Kifer
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions. NeurIPS (2023)
Yingtai Xiao, Guanlin He, Danfeng Zhang, Daniel Kifer
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions. CoRR (2023)
Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
An Empirical Analysis of Recurrent Learning Algorithms In Neural Lossy Image Compression Systems. CoRR (2022)
Ankur Arjun Mali, Alexander G. Ororbia II, Daniel Kifer, C. Lee Giles
Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder. DCC (2022)
Alexander Ororbia, Ankur Arjun Mali, C. Lee Giles, Daniel Kifer
Lifelong Neural Predictive Coding: Learning Cumulatively Online without Forgetting. NeurIPS (2022)
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
The 2020 Census Disclosure Avoidance System TopDown Algorithm. CoRR (2022)
Savinay Nagendra, Chaopeng Shen, Daniel Kifer
ThreshNet: Segmentation Refinement Inspired by Region-Specific Thresholding. CoRR (2022)
Savinay Nagendra, Daniel Kifer, Benjamin Mirus, Te Pei, Kathryn Lawson, Srikanth Banagere Manjunatha, Weixin Li, Hien Nguyen, Tong Qiu, Sarah Tran, Chaopeng Shen
Constructing a Large-Scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 15 (2022)
Prottay Protivash, John Durrell, Zeyu Ding, Danfeng Zhang, Daniel Kifer
Reconstruction Attacks on Aggressive Relaxations of Differential Privacy. CoRR (2022)
Brian Karrer, Daniel Kifer, Arjun Wilkins, Danfeng Zhang
Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism. CoRR (2022)
Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer
Answering Private Linear Queries Adaptively using the Common Mechanism. CoRR (2022)
Daniel Kifer, John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Philip Leclerc, Ashwin Machanavajjhala, William Sexton, Pavel Zhuravlev
Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census. CoRR (2022)
Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder. CoRR (2022)
John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Daniel Kifer, Philip Leclerc, Jeffrey Ocker, Michael Ratcliffe, Pavel Zhuravlev
Geographic Spines in the 2020 Census Disclosure Avoidance System TopDown Algorithm. CoRR (2022)
Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units. CoRR (2021)
Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
Recognizing Long Grammatical Sequences using Recurrent Networks Augmented with an External Differentiable Stack. ICGI (2021)
Yingtai Xiao, Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer
Optimizing Fitness-For-Use of Differentially Private Linear Queries. Proc. VLDB Endow. 14 (10) (2021)
Jaewoo Lee, Daniel Kifer
Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping. Proc. Priv. Enhancing Technol. 2021 (1) (2021)
Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles
Investigating Backpropagation Alternatives when Learning to Dynamically Count with Recurrent Neural Networks. ICGI (2021)
Yuxin Wang, Zeyu Ding, Yingtai Xiao, Daniel Kifer, Danfeng Zhang
DPGen: Automated Program Synthesis for Differential Privacy. CoRR (2021)
Shivansh Rao, Vikas Kumar, Daniel Kifer, C. Lee Giles, Ankur Arjun Mali
OmniLayout: Room Layout Reconstruction From Indoor Spherical Panoramas. CVPR Workshops (2021)
Yuxin Wang, Zeyu Ding, Yingtai Xiao, Daniel Kifer, Danfeng Zhang
DPGen: Automated Program Synthesis for Differential Privacy. CCS (2021)
Kuai Fang, Daniel Kifer, Kathryn Lawson, Dapeng Feng, Chaopeng Shen
The data synergy effects of time-series deep learning models in hydrology. CoRR (2021)
John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson L. Garfinkel, Daniel Kifer, Philip Leclerc, William Sexton, Ashley Simpson, Christine Task, Pavel Zhuravlev
An Uncertainty Principle is a Price of Privacy-Preserving Microdata. NeurIPS (2021)
Zeyu Ding, Daniel Kifer, Sayed M. Saghaian N. E., Thomas Steinke, Yuxin Wang, Yingtai Xiao, Danfeng Zhang
The Permute-and-Flip Mechanism is Identical to Report-Noisy-Max with Exponential Noise. CoRR (2021)
Shivansh Rao, Vikas Kumar, Daniel Kifer, C. Lee Giles, Ankur Arjun Mali
OmniLayout: Room Layout Reconstruction from Indoor Spherical Panoramas. CoRR (2021)
Ankur Arjun Mali, Alexander G. Ororbia II, Daniel Kifer, C. Lee Giles
Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units. AAAI (2021)
John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson L. Garfinkel, Daniel Kifer, Philip Leclerc, William Sexton, Ashley Simpson, Christine Task, Pavel Zhuravlev
An Uncertainty Principle is a Price of Privacy-Preserving Microdata. CoRR (2021)
Zeyu Ding, Yuxin Wang, Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer
Free Gap Estimates from the Exponential Mechanism, Sparse Vector, Noisy Max and Related Algorithms. CoRR (2020)
Jaewoo Lee, Daniel Kifer
Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping. CoRR (2020)
Yingtai Xiao, Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer
Optimizing Fitness-For-Use of Differentially Private Linear Queries. CoRR (2020)
Yuxin Wang, Zeyu Ding, Daniel Kifer, Danfeng Zhang
CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples. CCS (2020)
Yuxin Wang, Zeyu Ding, Daniel Kifer, Danfeng Zhang
CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples. CoRR (2020)
Daniel Kifer, Solomon Messing, Aaron Roth, Abhradeep Thakurta, Danfeng Zhang
Guidelines for Implementing and Auditing Differentially Private Systems. CoRR (2020)
Ke Yuan, Dafang He, Xiao Yang, Zhi Tang, Daniel Kifer, C. Lee Giles
Follow The Curve: Arbitrarily Oriented Scene Text Detection Using Key Points Spotting And Curve Prediction. ICME (2020)
Alexander Ororbia, Ankur Arjun Mali, Daniel Kifer, C. Lee Giles
Reducing the Computational Burden of Deep Learning with Recursive Local Representation Alignment. CoRR (2020)
Alexander Ororbia, Ankur Arjun Mali, C. Lee Giles, Daniel Kifer
Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations. IEEE Trans. Neural Networks Learn. Syst. 31 (10) (2020)
Alexander Ororbia, Daniel Kifer
The Neural Coding Framework for Learning Generative Models. CoRR (2020)
Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, Clyde Lee Giles
Recognizing Long Grammatical Sequences Using Recurrent Networks Augmented With An External Differentiable Stack. CoRR (2020)
Jaewoo Lee, Daniel Kifer
Differentially Private Deep Learning with Direct Feedback Alignment. CoRR (2020)
Xiao Yang, Madian Khabsa, Miaosen Wang, Wei Wang, Ahmed Hassan Awadallah, Daniel Kifer, C. Lee Giles
Adversarial Training for Community Question Answer Selection Based on Multi-Scale Matching. AAAI (2019)
Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer
Free Gap Information from the Differentially Private Sparse Vector and Noisy Max Mechanisms. CoRR (2019)
Yuxin Wang, Zeyu Ding, Guanhong Wang, Daniel Kifer, Danfeng Zhang
Proving Differential Privacy with Shadow Execution. CoRR (2019)
Xiao Yang, Dafang He, Daniel Kifer, C. Lee Giles
A Learning-based Text Synthesis Engine for Scene Text Detection. BMVC (2019)
Alexander Ororbia, Ankur Arjun Mali, Daniel Kifer, C. Lee Giles
Lifelong Neural Predictive Coding: Sparsity Yields Less Forgetting when Learning Cumulatively. CoRR (2019)
Songshan Yang, Jiawei Wen, Xiang Zhan, Daniel Kifer
ET-Lasso: A New Efficient Tuning of Lasso-type Regularization for High-Dimensional Data. KDD (2019)
Hongjian Wang, Xianfeng Tang, Yu-Hsuan Kuo, Daniel Kifer, Zhenhui Li
A Simple Baseline for Travel Time Estimation using Large-scale Trip Data. ACM Trans. Intell. Syst. Technol. 10 (2) (2019)
Hongjian Wang, Huaxiu Yao, Daniel Kifer, Corina Graif, Zhenhui Li
Non-Stationary Model for Crime Rate Inference Using Modern Urban Data. IEEE Trans. Big Data 5 (2) (2019)
Yue Wang, Daniel Kifer, Jaewoo Lee
Differentially Private Confidence Intervals for Empirical Risk Minimization. J. Priv. Confidentiality 9 (1) (2019)
Yuxin Wang, Zeyu Ding, Guanhong Wang, Daniel Kifer, Danfeng Zhang
Proving differential privacy with shadow execution. PLDI (2019)
Kuai Fang, Chaopeng Shen, Daniel Kifer
Evaluating aleatoric and epistemic uncertainties of time series deep learning models for soil moisture predictions. CoRR (2019)
Alexander G. Ororbia II, Ankur Arjun Mali, Daniel Kifer, C. Lee Giles
Conducting Credit Assignment by Aligning Local Representations. CoRR (2018)
Jaewoo Lee, Daniel Kifer
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget. KDD (2018)
Alexander Ororbia, Ankur Arjun Mali, C. Lee Giles, Daniel Kifer
Online Learning of Recurrent Neural Architectures by Locally Aligning Distributed Representations. CoRR (2018)
Dafang He, Xiao Yang, Daniel Kifer, C. Lee Giles
TextContourNet: a Flexible and Effective Framework for Improving Scene Text Detection Architecture with a Multi-task Cascade. CoRR (2018)
Dafang He, Yeqing Li, Alexander N. Gorban, Derrall Heath, Julian Ibarz, Qian Yu, Daniel Kifer, C. Lee Giles
Large Scale Scene Text Verification with Guided Attention. ACCV (5) (2018)
Dafang He, Yeqing Li, Alexander N. Gorban, Derrall Heath, Julian Ibarz, Qian Yu, Daniel Kifer, C. Lee Giles
Guided Attention for Large Scale Scene Text Verification. CoRR (2018)
Yu-Hsuan Kuo, Cho-Chun Chiu, Daniel Kifer, Michael Hay, Ashwin Machanavajjhala
Differentially Private Hierarchical Group Size Estimation. CoRR (2018)
Ding Ding, Yuxin Wang, Guanhong Wang, Danfeng Zhang, Daniel Kifer
Toward Detecting Violations of Differential Privacy. CoRR (2018)
Yu-Hsuan Kuo, Zhenhui Li, Daniel Kifer
Detecting Outliers in Data with Correlated Measures. CIKM (2018)
Yue Wang, Daniel Kifer, Jaewoo Lee
Differentially Private Confidence Intervals for Empirical Risk Minimization. CoRR (2018)
Songshan Yang, Jiawei Wen, Xiang Zhan, Daniel Kifer
ET-Lasso: Efficient Tuning of Lasso for High-Dimensional Data. CoRR (2018)
Zeyu Ding, Yuxin Wang, Guanhong Wang, Danfeng Zhang, Daniel Kifer
Detecting Violations of Differential Privacy. CCS (2018)
Yu-Hsuan Kuo, Zhenhui Li, Daniel Kifer
Detecting Outliers in Data with Correlated Measures. CoRR (2018)
Yue Wang, Daniel Kifer, Jaewoo Lee, Vishesh Karwa
Statistical Approximating Distributions Under Differential Privacy. J. Priv. Confidentiality 8 (1) (2018)
Yu-Hsuan Kuo, Cho-Chun Chiu, Daniel Kifer, Michael Hay, Ashwin Machanavajjhala
Differentially Private Hierarchical Count-of-Counts Histograms. Proc. VLDB Endow. 11 (11) (2018)
Jaewoo Lee, Daniel Kifer
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget. CoRR (2018)
Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, C. Lee Giles
Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Networks. CVPR (2017)
Omar Montasser, Daniel Kifer
Predicting Demographics of High-Resolution Geographies with Geotagged Tweets. CoRR (2017)
Dafang He, Xiao Yang, Chen Liang, Zihan Zhou, Alexander G. Ororbia II, Daniel Kifer, C. Lee Giles
Multi-scale FCN with Cascaded Instance Aware Segmentation for Arbitrary Oriented Word Spotting in the Wild. CVPR (2017)
Ryan Rogers, Daniel Kifer
A New Class of Private Chi-Square Hypothesis Tests. AISTATS (2017)
Omar Montasser, Daniel Kifer
Predicting Demographics of High-Resolution Geographies with Geotagged Tweets. AAAI (2017)
Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles
Improving Offline Handwritten Chinese Character Recognition by Iterative Refinement. ICDAR (2017)
Danfeng Zhang, Daniel Kifer
LightDP: towards automating differential privacy proofs. POPL (2017)
Xiao Yang, Dafang He, Wenyi Huang, Alexander Ororbia, Zihan Zhou, Daniel Kifer, C. Lee Giles
Smart Library: Identifying Books on Library Shelves Using Supervised Deep Learning for Scene Text Reading. JCDL (2017)
Xiao Yang, Mehmet Ersin Yümer, Paul Asente, Mike Kraley, Daniel Kifer, C. Lee Giles
Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Network. CoRR (2017)
Dafang He, Scott Cohen, Brian L. Price, Daniel Kifer, C. Lee Giles
Multi-Scale Multi-Task FCN for Semantic Page Segmentation and Table Detection. ICDAR (2017)
Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles
Learning to Read Irregular Text with Attention Mechanisms. IJCAI (2017)
Alexander G. Ororbia II, Daniel Kifer, C. Lee Giles
Unifying Adversarial Training Algorithms with Data Gradient Regularization. Neural Comput. 29 (4) (2017)
Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li
Crime Rate Inference with Big Data. KDD (2016)
Alexander G. Ororbia II, C. Lee Giles, Daniel Kifer
Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization. CoRR (2016)
Jaewoo Lee, Daniel Kifer
Postprocessing for Iterative Differentially Private Algorithms. CoRR (2016)
Danfeng Zhang, Daniel Kifer
AutoPriv: Automating Differential Privacy Proofs. CoRR (2016)
Wenyi Huang, Dafang He, Xiao Yang, Zihan Zhou, Daniel Kifer, C. Lee Giles
Detecting Arbitrary Oriented Text in the Wild with a Visual Attention Model. ACM Multimedia (2016)
Daniel Kifer, Ryan Rogers
A New Class of Private Chi-Square Tests. CoRR (2016)
Hongjian Wang, Yu-Hsuan Kuo, Daniel Kifer, Zhenhui Li
A simple baseline for travel time estimation using large-scale trip data. SIGSPATIAL/GIS (2016)
Dafang He, Xiao Yang, Wenyi Huang, Zihan Zhou, Daniel Kifer, C. Lee Giles
Aggregating Local Context for Accurate Scene Text Detection. ACCV (5) (2016)
Bing-Rong Lin, Daniel Kifer
Information Measures in Statistical Privacy and Data Processing Applications. ACM Trans. Knowl. Discov. Data 9 (4) (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Daniel Kifer