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 10/9  | Side channels and implementation issues <br> **Reading:** [*On Significance of the Least Significant Bits For Differential Privacy*](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.366.5957&rep=rep1&type=pdf) | JH | --- |
 10/11 | Model watermarking <br> **Reading:** [*Protecting Intellectual Property of Deep Neural Networks with Watermarking*](https://gzs715.github.io/pubs/WATERMARK_ASIACCS18.pdf) <br> **Reading:** [*Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring*](https://arxiv.org/pdf/1802.04633) | Noor/Shashank | Joseph/Nils | MS1 Due
       | <center> <h4> **Algorithmic Fairness** </h4> </center> | | |
-10/14 | Overview and basic notions <br> **See also:** [Barocas, Hardt, and Narayanan](https://fairmlbook.org/index.html), Chapter 1-2 | JH | --- |
+10/14 | Overview and basic notions <br> **Reading:** [Barocas, Hardt, and Narayanan](https://fairmlbook.org/index.html), Chapter 1-2 | JH | --- |
 10/16 | Individual and group fairness <br> **Reading:** [*Fairness through Awarness*](https://arxiv.org/pdf/1104.3913) <br> **Reading:** [*Equality of Opportunity in Supervised Learning*](https://arxiv.org/pdf/1610.02413) | JH | Jack/Jack |
 10/18 | Inherent tradeoffs <br> **Reading:** [*Inherent Trade-Offs in the Fair Determination of Risk Scores*](https://arxiv.org/pdf/1609.05807) | Bobby | --- |
-10/21 | Defining fairness: challenges <br> **Reading:** [*50 Years of Test (Un)fairness: Lessons for Machine Learning*](https://arxiv.org/pdf/1811.10104) | JH | Bobby |
+10/21 | Defining fairness: challenges <br> **Reading:** [*50 Years of Test (Un)fairness: Lessons for Machine Learning*](https://arxiv.org/pdf/1811.10104) <br> **Reading:** [Barocas, Hardt, and Narayanan](https://fairmlbook.org/causal.html), Chapter 4 | JH | Bobby |
 10/23 | Fairness in unsupervised learning <br> **Reading:** [*Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings*](https://arxiv.org/pdf/1607.06520) <br> **Reading:** [*Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints*](https://arxiv.org/pdf/1707.09457) | Zach/Jialu | Noor/Shashank |
-10/25 | Beyond observational measures <br> **Reading:** [*Avoiding Discrimination through Causal Reasoning*](https://arxiv.org/pdf/1706.02744) <br> **Reading:** [*Counterfactual Fairness*](https://arxiv.org/pdf/1703.06856) <br> **See also:** [Barocas, Hardt, and Narayanan](https://fairmlbook.org/causal.html), Chapter 4 | Nat/Geetika | Varun/Vibhor/Adarsh |
+10/25 | Beyond observational measures <br> **Reading:** [*Avoiding Discrimination through Causal Reasoning*](https://arxiv.org/pdf/1706.02744) <br> **Reading:** [*Counterfactual Fairness*](https://arxiv.org/pdf/1703.06856) | Nat/Geetika | Varun/Vibhor/Adarsh |
       | <center> <h4> **PL and Verification** </h4> </center> | | |
 10/28 | Overview and basic notions | JH | --- |
 10/30 | Probabilistic programming languages <br> **Reading:** [*Probabilistic Programming*](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/fose-icse2014.pdf) | Miru/Pierre | Nat/Geetika |