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ORCIDDaniel Kifer
Dan Kifer
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- affiliation: Pennsylvania State University, University Park, USA
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2020 – today
- 2024
[c62]Savinay Nagendra, Daniel Kifer:
PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise Binarization. WACV 2024: 1350-1361- [i65]Neisarg Dave, Daniel Kifer, C. Lee Giles, Ankur Mali:
Stability Analysis of Various Symbolic Rule Extraction Methods from Recurrent Neural Network. CoRR abs/2402.02627 (2024) - [i64]Neisarg Dave, Daniel Kifer, C. Lee Giles, Ankur Mali:
Investigating Symbolic Capabilities of Large Language Models. CoRR abs/2405.13209 (2024) - [i63]Yingtai Xiao, Jian Du, Shikun Zhang, Qiang Yan, Danfeng Zhang, Daniel Kifer:
Click Without Compromise: Online Advertising Measurement via Per User Differential Privacy. CoRR abs/2406.02463 (2024) - [i62]Brett Mullins, Miguel Fuentes, Yingtai Xiao, Daniel Kifer, Cameron Musco, Daniel Sheldon:
Efficient and Private Marginal Reconstruction with Local Non-Negativity. CoRR abs/2410.01091 (2024) - [i61]Neisarg Dave, Daniel Kifer, C. Lee Giles, Ankur Arjun Mali:
Precision, Stability, and Generalization: A Comprehensive Assessment of RNNs learnability capability for Classifying Counter and Dyck Languages. CoRR abs/2410.03118 (2024) - 2023
- [j26]Yingtai Xiao, Guanhong Wang, Danfeng Zhang
, Daniel Kifer:
Answering Private Linear Queries Adaptively using the Common Mechanism. Proc. VLDB Endow. 16(8): 1883-1896 (2023) - [j25]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): 23-48 (2023) - [c61]Alexander G. Ororbia II, Ankur Arjun Mali, Daniel Kifer, C. Lee Giles:
Backpropagation-Free Deep Learning with Recursive Local Representation Alignment. AAAI 2023: 9327-9335 - [c60]Yingtai Xiao, Guanlin He, Danfeng Zhang, Daniel Kifer:
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions. NeurIPS 2023 - [i60]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 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:
Differentiable modeling to unify machine learning and physical models and advance Geosciences. CoRR abs/2301.04027 (2023) - [i59]Yingtai Xiao, Guanlin He, Danfeng Zhang, Daniel Kifer:
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions. CoRR abs/2305.08175 (2023) - [i58]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 abs/2308.08057 (2023) - [i57]Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles:
On the Tensor Representation and Algebraic Homomorphism of the Neural State Turing Machine. CoRR abs/2309.14690 (2023) - [i56]Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles:
On the Computational Complexity and Formal Hierarchy of Second Order Recurrent Neural Networks. CoRR abs/2309.14691 (2023) - [i55]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 abs/2310.09398 (2023) - [i54]Savinay Nagendra, Chaopeng Shen, Daniel Kifer:
Estimating Uncertainty in Landslide Segmentation Models. CoRR abs/2311.11138 (2023) - [i53]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 abs/2312.10863 (2023) - [i52]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 abs/2312.11283 (2023) - 2022
- [j24]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: 4349-4370 (2022) - [c59]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: 471 - [c58]Alexander Ororbia, Ankur Arjun Mali, C. Lee Giles, Daniel Kifer:
Lifelong Neural Predictive Coding: Learning Cumulatively Online without Forgetting. NeurIPS 2022 - [i51]Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles:
An Empirical Analysis of Recurrent Learning Algorithms In Neural Lossy Image Compression Systems. CoRR abs/2201.11782 (2022) - [i50]Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles:
Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder. CoRR abs/2201.11795 (2022) - [i49]Brian Karrer, Daniel Kifer, Arjun Wilkins, Danfeng Zhang:
Exact Privacy Analysis of the Gaussian Sparse Histogram Mechanism. CoRR abs/2202.01100 (2022) - [i48]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 abs/2203.16654 (2022) - [i47]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 abs/2204.08986 (2022) - [i46]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 abs/2209.03310 (2022) - [i45]Prottay Protivash, John Durrell, Zeyu Ding, Danfeng Zhang, Daniel Kifer:
Reconstruction Attacks on Aggressive Relaxations of Differential Privacy. CoRR abs/2209.03905 (2022) - [i44]Savinay Nagendra, Chaopeng Shen, Daniel Kifer:
ThreshNet: Segmentation Refinement Inspired by Region-Specific Thresholding. CoRR abs/2211.06560 (2022) - [i43]Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer:
Answering Private Linear Queries Adaptively using the Common Mechanism. CoRR abs/2212.00135 (2022) - 2021
- [j23]Jaewoo Lee, Daniel Kifer:
Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping. Proc. Priv. Enhancing Technol. 2021(1): 128-144 (2021) - [j22]Yingtai Xiao, Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer:
Optimizing Fitness-For-Use of Differentially Private Linear Queries. Proc. VLDB Endow. 14(10): 1730-1742 (2021) - [c57]Ankur Arjun Mali, Alexander G. Ororbia II, Daniel Kifer, C. Lee Giles:
Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units. AAAI 2021: 5006-5015 - [c56]Yuxin Wang, Zeyu Ding, Yingtai Xiao, Daniel Kifer, Danfeng Zhang:
DPGen: Automated Program Synthesis for Differential Privacy. CCS 2021: 393-411 - [c55]Shivansh Rao, Vikas Kumar, Daniel Kifer, C. Lee Giles, Ankur Arjun Mali:
OmniLayout: Room Layout Reconstruction From Indoor Spherical Panoramas. CVPR Workshops 2021: 3706-3715 - [c54]Ankur Arjun Mali, Alexander G. Ororbia II, Dan Kifer, C. Lee Giles:
An Empirical Analysis of Recurrent Learning Algorithms in Neural Lossy Image Compression Systems. DCC 2021: 356 - [c53]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: 130-153 - [c52]Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles:
Investigating Backpropagation Alternatives when Learning to Dynamically Count with Recurrent Neural Networks. ICGI 2021: 154-175 - [c51]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: 11883-11895 - [i42]Kuai Fang, Daniel Kifer, Kathryn Lawson, Dapeng Feng, Chaopeng Shen:
The data synergy effects of time-series deep learning models in hydrology. CoRR abs/2101.01876 (2021) - [i41]Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, C. Lee Giles:
Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units. CoRR abs/2104.02899 (2021) - [i40]Shivansh Rao, Vikas Kumar, Daniel Kifer, C. Lee Giles, Ankur Arjun Mali:
OmniLayout: Room Layout Reconstruction from Indoor Spherical Panoramas. CoRR abs/2104.09403 (2021) - [i39]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 abs/2105.07260 (2021) - [i38]Yuxin Wang, Zeyu Ding, Yingtai Xiao, Daniel Kifer, Danfeng Zhang:
DPGen: Automated Program Synthesis for Differential Privacy. CoRR abs/2109.07441 (2021) - [i37]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 abs/2110.13239 (2021) - 2020
- [j21]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): 4267-4278 (2020) - [c50]Yuxin Wang, Zeyu Ding, Daniel Kifer, Danfeng Zhang:
CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples. CCS 2020: 919-938 - [c49]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: 1-6 - [i36]Alexander Ororbia, Ankur Arjun Mali, Daniel Kifer, C. Lee Giles:
Reducing the Computational Burden of Deep Learning with Recursive Local Representation Alignment. CoRR abs/2002.03911 (2020) - [i35]Daniel Kifer, Solomon Messing, Aaron Roth, Abhradeep Thakurta, Danfeng Zhang:
Guidelines for Implementing and Auditing Differentially Private Systems. CoRR abs/2002.04049 (2020) - [i34]Ankur Arjun Mali, Alexander Ororbia, Daniel Kifer, Clyde Lee Giles:
Recognizing Long Grammatical Sequences Using Recurrent Networks Augmented With An External Differentiable Stack. CoRR abs/2004.07623 (2020) - [i33]Yuxin Wang, Zeyu Ding, Daniel Kifer, Danfeng Zhang:
CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples. CoRR abs/2008.07485 (2020) - [i32]Jaewoo Lee, Daniel Kifer:
Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping. CoRR abs/2009.03106 (2020) - [i31]Jaewoo Lee, Daniel Kifer:
Differentially Private Deep Learning with Direct Feedback Alignment. CoRR abs/2010.03701 (2020) - [i30]Yingtai Xiao, Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer:
Optimizing Fitness-For-Use of Differentially Private Linear Queries. CoRR abs/2012.00135 (2020) - [i29]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 abs/2012.01592 (2020) - [i28]Alexander Ororbia, Daniel Kifer:
The Neural Coding Framework for Learning Generative Models. CoRR abs/2012.03405 (2020)
2010 – 2019
- 2019
- [j20]Yue Wang, Daniel Kifer, Jaewoo Lee:
Differentially Private Confidence Intervals for Empirical Risk Minimization. J. Priv. Confidentiality 9(1) (2019) - [j19]Zeyu Ding, Yuxin Wang, Danfeng Zhang, Dan Kifer:
Free Gap Information from the Differentially Private Sparse Vector and Noisy Max Mechanisms. Proc. VLDB Endow. 13(3): 293-306 (2019) - [j18]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): 180-194 (2019) - [j17]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): 19:1-19:22 (2019) - [c48]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: 395-402 - [c47]Chen Chen, Jaewoo Lee, Dan Kifer:
Renyi Differentially Private ERM for Smooth Objectives. AISTATS 2019: 2037-2046 - [c46]Xiao Yang, Dafang He, Daniel Kifer, C. Lee Giles:
A Learning-based Text Synthesis Engine for Scene Text Detection. BMVC 2019: 94 - [c45]Anand Gopalakrishnan, Ankur Arjun Mali, Dan Kifer, C. Lee Giles, Alexander G. Ororbia II:
A Neural Temporal Model for Human Motion Prediction. CVPR 2019: 12116-12125 - [c44]Songshan Yang, Jiawei Wen, Xiang Zhan, Daniel Kifer:
ET-Lasso: A New Efficient Tuning of Lasso-type Regularization for High-Dimensional Data. KDD 2019: 607-616 - [c43]Yuxin Wang, Zeyu Ding, Guanhong Wang, Daniel Kifer, Danfeng Zhang:
Proving differential privacy with shadow execution. PLDI 2019: 655-669 - [c42]Dafang He, Xiao Yang, Dan Kifer, C. Lee Giles:
TextContourNet: A Flexible and Effective Framework for Improving Scene Text Detection Architecture With a Multi-Task Cascade. WACV 2019: 676-685 - [i27]Yuxin Wang, Zeyu Ding, Guanhong Wang, Daniel Kifer, Danfeng Zhang:
Proving Differential Privacy with Shadow Execution. CoRR abs/1903.12254 (2019) - [i26]Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer:
Free Gap Information from the Differentially Private Sparse Vector and Noisy Max Mechanisms. CoRR abs/1904.12773 (2019) - [i25]Alexander Ororbia, Ankur Arjun Mali, Daniel Kifer, C. Lee Giles:
Lifelong Neural Predictive Coding: Sparsity Yields Less Forgetting when Learning Cumulatively. CoRR abs/1905.10696 (2019) - [i24]Kuai Fang, Chaopeng Shen, Daniel Kifer:
Evaluating aleatoric and epistemic uncertainties of time series deep learning models for soil moisture predictions. CoRR abs/1906.04595 (2019) - 2018
- [j16]Dan Kifer:
Reminiscenses of Steve Fienberg. J. Priv. Confidentiality 8(1) (2018) - [j15]Yue Wang, Daniel Kifer, Jaewoo Lee, Vishesh Karwa:
Statistical Approximating Distributions Under Differential Privacy. J. Priv. Confidentiality 8(1) (2018) - [j14]Yu-Hsuan Kuo, Cho-Chun Chiu, Daniel Kifer, Michael Hay, Ashwin Machanavajjhala:
Differentially Private Hierarchical Count-of-Counts Histograms. Proc. VLDB Endow. 11(11): 1509-1521 (2018) - [c41]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: 260-275 - [c40]Zeyu Ding, Yuxin Wang, Guanhong Wang, Danfeng Zhang, Daniel Kifer:
Detecting Violations of Differential Privacy. CCS 2018: 475-489 - [c39]Yu-Hsuan Kuo, Zhenhui Li, Daniel Kifer:
Detecting Outliers in Data with Correlated Measures. CIKM 2018: 287-296 - [c38]Jaewoo Lee, Daniel Kifer:
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget. KDD 2018: 1656-1665 - [r2]Daniel Kifer:
Change Detection on Streams. Encyclopedia of Database Systems (2nd ed.) 2018 - [i23]Alexander G. Ororbia II, Ankur Arjun Mali, Daniel Kifer, C. Lee Giles:
Conducting Credit Assignment by Aligning Local Representations. CoRR abs/1803.01834 (2018) - [i22]Yu-Hsuan Kuo, Cho-Chun Chiu, Daniel Kifer, Michael Hay, Ashwin Machanavajjhala:
Differentially Private Hierarchical Group Size Estimation. CoRR abs/1804.00370 (2018) - [i21]Yue Wang, Daniel Kifer, Jaewoo Lee:
Differentially Private Confidence Intervals for Empirical Risk Minimization. CoRR abs/1804.03794 (2018) - [i20]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 abs/1804.08588 (2018) - [i19]Ding Ding, Yuxin Wang, Guanhong Wang, Danfeng Zhang, Daniel Kifer:
Toward Detecting Violations of Differential Privacy. CoRR abs/1805.10277 (2018) - [i18]Yu-Hsuan Kuo, Zhenhui Li, Daniel Kifer:
Detecting Outliers in Data with Correlated Measures. CoRR abs/1808.08640 (2018) - [i17]Jaewoo Lee, Daniel Kifer:
Concentrated Differentially Private Gradient Descent with Adaptive per-Iteration Privacy Budget. CoRR abs/1808.09501 (2018) - [i16]Anand Gopalakrishnan, Ankur Arjun Mali, Dan Kifer, C. Lee Giles, Alexander G. Ororbia II:
A Neural Temporal Model for Human Motion Prediction. CoRR abs/1809.03036 (2018) - [i15]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 abs/1809.03050 (2018) - [i14]Songshan Yang, Jiawei Wen, Xiang Zhan, Daniel Kifer:
ET-Lasso: Efficient Tuning of Lasso for High-Dimensional Data. CoRR abs/1810.04513 (2018) - [i13]Alexander Ororbia, Ankur Arjun Mali, C. Lee Giles, Daniel Kifer:
Online Learning of Recurrent Neural Architectures by Locally Aligning Distributed Representations. CoRR abs/1810.07411 (2018) - 2017
- [j13]Alexander G. Ororbia II, Daniel Kifer, C. Lee Giles:
Unifying Adversarial Training Algorithms with Data Gradient Regularization. Neural Comput. 29(4): 867-887 (2017) - [c37]Omar Montasser, Daniel Kifer:
Predicting Demographics of High-Resolution Geographies with Geotagged Tweets. AAAI 2017: 1460-1466 - [c36]Ryan Rogers, Daniel Kifer:
A New Class of Private Chi-Square Hypothesis Tests. AISTATS 2017: 991-1000 - [c35]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: 474-483 - [c34]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: 4342-4351 - [c33]Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles:
Improving Offline Handwritten Chinese Character Recognition by Iterative Refinement. ICDAR 2017: 5-10 - [c32]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: 254-261 - [c31]Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles:
Learning to Read Irregular Text with Attention Mechanisms. IJCAI 2017: 3280-3286 - [c30]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: 245-248 - [c29]Danfeng Zhang, Daniel Kifer:
LightDP: towards automating differential privacy proofs. POPL 2017: 888-901 - [i12]Omar Montasser, Daniel Kifer:
Predicting Demographics of High-Resolution Geographies with Geotagged Tweets. CoRR abs/1701.06225 (2017) - [i11]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 abs/1706.02337 (2017) - 2016
- [c28]Dafang He, Xiao Yang, Wenyi Huang, Zihan Zhou, Daniel Kifer, C. Lee Giles:
Aggregating Local Context for Accurate Scene Text Detection. ACCV (5) 2016: 280-296 - [c27]Hongjian Wang, Yu-Hsuan Kuo, Daniel Kifer, Zhenhui Li:
A simple baseline for travel time estimation using large-scale trip data. SIGSPATIAL/GIS 2016: 61:1-61:4 - [c26]Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li:
Crime Rate Inference with Big Data. KDD 2016: 635-644 - [c25]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: 551-555 - [i10]Alexander G. Ororbia II, C. Lee Giles, Daniel Kifer:
Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization. CoRR abs/1601.07213 (2016) - [i9]Danfeng Zhang, Daniel Kifer:
AutoPriv: Automating Differential Privacy Proofs. CoRR abs/1607.08228 (2016) - [i8]Jaewoo Lee, Daniel Kifer:
Postprocessing for Iterative Differentially Private Algorithms. CoRR abs/1609.03251 (2016) - [i7]Daniel Kifer, Ryan Rogers:
A New Class of Private Chi-Square Tests. CoRR abs/1610.07662 (2016) - [i6]Xiao Yang, Dafang He, Wenyi Huang, Zihan Zhou, Alexander Ororbia, Dan Kifer, C. Lee Giles:
Smart Library: Identifying Books in a Library using Richly Supervised Deep Scene Text Reading. CoRR abs/1611.07385 (2016) - 2015
- [j12]Ashwin Machanavajjhala, Daniel Kifer:
Designing statistical privacy for your data. Commun. ACM 58(3): 58-67 (2015) - [j11]Bing-Rong Lin, Daniel Kifer:
Information Measures in Statistical Privacy and Data Processing Applications. ACM Trans. Knowl. Discov. Data 9(4): 28:1-28:29 (2015) - [c24]Daniel Kifer:
On Estimating the Swapping Rate for Categorical Data. KDD 2015: 557-566 - [c23]Jaewoo Lee, Yue Wang, Daniel Kifer:
Maximum Likelihood Postprocessing for Differential Privacy under Consistency Constraints. KDD 2015: 635-644 - [c22]Daniel Kifer:
Privacy and the Price of Data. LICS 2015: 16 - [i5]Yue Wang, Jaewoo Lee, Daniel Kifer:
Differentially Private Hypothesis Testing, Revisited. CoRR abs/1511.03376 (2015) - [i4]Vishesh Karwa, Dan Kifer, Aleksandra B. Slavkovic:
Private Posterior distributions from Variational approximations. CoRR abs/1511.07896 (2015) - [i3]Hongjian Wang, Zhenhui Li, Yu-Hsuan Kuo, Dan Kifer:
A Simple Baseline for Travel Time Estimation using Large-Scale Trip Data. CoRR abs/1512.08580 (2015) - 2014
- [j10]Bing-Rong Lin, Dan Kifer:
Towards a Systematic Analysis of Privacy Definitions. J. Priv. Confidentiality 5(2) (2014) - [j9]Bing-Rong Lin, Daniel Kifer:
On Arbitrage-free Pricing for General Data Queries. Proc. VLDB Endow. 7(9): 757-768 (2014) - [j8]Daniel Kifer, Ashwin Machanavajjhala:
Pufferfish: A framework for mathematical privacy definitions. ACM Trans. Database Syst. 39(1): 3:1-3:36 (2014) - 2013
- [j7]Dan Kifer:
Introduction to Special Section. J. Priv. Confidentiality 5(1) (2013) - [c21]Sirinda Palahan, Domagoj Babic, Swarat Chaudhuri, Daniel Kifer:
Extraction of statistically significant malware behaviors. ACSAC 2013: 69-78 - [c20]Bing-Rong Lin, Daniel Kifer:
Geometry of privacy and utility. GlobalSIP 2013: 281-284 - [c19]Bing-Rong Lin, Daniel Kifer:
Information preservation in statistical privacy and bayesian estimation of unattributed histograms. SIGMOD Conference 2013: 677-688 - 2012
- [j6]Daniel Kifer, Bing-Rong Lin:
An Axiomatic View of Statistical Privacy and Utility. J. Priv. Confidentiality 4(1) (2012) - [c18]Bing-Rong Lin, Daniel Kifer:
Reasoning about privacy using axioms. ACSCC 2012: 975-979 - [c17]Daniel Kifer, Ashwin Machanavajjhala:
A rigorous and customizable framework for privacy. PODS 2012: 77-88 - [c16]Daniel Kifer, Adam D. Smith, Abhradeep Thakurta:
Private Convex Optimization for Empirical Risk Minimization with Applications to High-dimensional Regression. COLT 2012: 25.1-25.40 - [i2]Bing-Rong Lin, Daniel Kifer:
A Framework for Extracting Semantic Guarantees from Privacy. CoRR abs/1208.5443 (2012) - 2011
- [c15]Daniel Kifer, Ashwin Machanavajjhala:
No free lunch in data privacy. SIGMOD Conference 2011: 193-204 - [c14]Qi He, Daniel Kifer, Jian Pei, Prasenjit Mitra, C. Lee Giles:
Citation recommendation without author supervision. WSDM 2011: 755-764 - 2010
- [c13]Bi Chen, Leilei Zhu, Daniel Kifer, Dongwon Lee:
What Is an Opinion About? Exploring Political Standpoints Using Opinion Scoring Model. AAAI 2010: 1007-1012 - [c12]Johannes Gehrke, Daniel Kifer, Ashwin Machanavajjhala:
Privacy in data publishing. ICDE 2010: 1213 - [c11]Daniel Kifer, Bing-Rong Lin:
Towards an axiomatization of statistical privacy and utility. PODS 2010: 147-158 - [c10]Qi He, Jian Pei, Daniel Kifer, Prasenjit Mitra, C. Lee Giles:
Context-aware citation recommendation. WWW 2010: 421-430
2000 – 2009
- 2009
- [j5]Bee-Chung Chen, Daniel Kifer, Kristen LeFevre, Ashwin Machanavajjhala:
Privacy-Preserving Data Publishing. Found. Trends Databases 2(1-2): 1-167 (2009) - [c9]Daniel Kifer:
Attacks on privacy and deFinetti's theorem. SIGMOD Conference 2009: 127-138 - [r1]Daniel Kifer:
Change Detection on Streams. Encyclopedia of Database Systems 2009: 317-321 - 2008
- [j4]Parag Agrawal, Daniel Kifer, Christopher Olston:
Scheduling shared scans of large data files. Proc. VLDB Endow. 1(1): 958-969 (2008) - [c8]Ashwin Machanavajjhala, Daniel Kifer, John M. Abowd, Johannes Gehrke, Lars Vilhuber:
Privacy: Theory meets Practice on the Map. ICDE 2008: 277-286 - 2007
- [j3]Ashwin Machanavajjhala, Daniel Kifer, Johannes Gehrke, Muthuramakrishnan Venkitasubramaniam:
L-diversity: Privacy beyond k-anonymity. ACM Trans. Knowl. Discov. Data 1(1): 3 (2007) - [c7]David J. Martin, Daniel Kifer, Ashwin Machanavajjhala, Johannes Gehrke, Joseph Y. Halpern:
Worst-Case Background Knowledge for Privacy-Preserving Data Publishing. ICDE 2007: 126-135 - [i1]David J. Martin, Daniel Kifer, Ashwin Machanavajjhala, Johannes Gehrke, Joseph Y. Halpern:
Worst-Case Background Knowledge for Privacy-Preserving Data Publishing. CoRR abs/0705.2787 (2007) - 2006
- [b1]Dan Kifer:
Graphs and Privacy. Cornell University, USA, 2006 - [c6]Ashwin Machanavajjhala, Johannes Gehrke, Daniel Kifer, Muthuramakrishnan Venkitasubramaniam:
l-Diversity: Privacy Beyond k-Anonymity. ICDE 2006: 24 - [c5]Daniel Kifer, Johannes Gehrke:
Injecting utility into anonymized datasets. SIGMOD Conference 2006: 217-228 - 2004
- [j2]Manuel Calimlim, Jim Cordes, Alan J. Demers, Julia Deneva, Johannes Gehrke, Daniel Kifer, Mirek Riedewald, Jayavel Shanmugasundaram:
A Vision for PetaByte Data Management and Analyis Services for the Arecibo Telescope. IEEE Data Eng. Bull. 27(4): 12-20 (2004) - [c4]Daniel Kifer, Johannes Gehrke, Cristian Bucila, Walker M. White:
How to Quickly Find a Witness. Constraint-Based Mining and Inductive Databases 2004: 216-242 - [c3]Daniel Kifer, Shai Ben-David, Johannes Gehrke:
Detecting Change in Data Streams. VLDB 2004: 180-191 - 2003
- [j1]Cristian Bucila, Johannes Gehrke, Daniel Kifer, Walker M. White:
DualMiner: A Dual-Pruning Algorithm for Itemsets with Constraints. Data Min. Knowl. Discov. 7(3): 241-272 (2003) - [c2]Daniel Kifer, Johannes Gehrke, Cristian Bucila, Walker M. White:
How to quickly find a witness. PODS 2003: 272-283 - 2002
- [c1]Cristian Bucila, Johannes Gehrke, Daniel Kifer, Walker M. White:
DualMiner: a dual-pruning algorithm for itemsets with constraints. KDD 2002: 42-51
Coauthor Index
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